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Jonas Zeunert
2025-07-18 22:22:32 +02:00
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 Awesome Data Engineering !Awesome (https://awesome.re/badge-flat2.svg) (https://github.com/sindresorhus/awesome)
 Awesome Data Engineering !Awesome (https://awesome.re/badge-flat2.svg) (https://github.com/sindresorhus/awesome)
▐ A curated list of awesome things related to Data Engineering.
@@ -28,6 +28,7 @@
 - Forums (#forums)
 - Conferences (#conferences)
 - Podcasts (#podcasts)
 - Books (#books)
Databases
@@ -61,8 +62,8 @@
 - ClickHouse (https://clickhouse.tech) - Distributed columnar DBMS for OLAP. SQL.
- Document
 - MongoDB (https://www.mongodb.com) - An open-source, document database designed for ease of development and scaling.
- **Percona Server for MongoDB** (https://www.percona.com/software/mongo-database/percona-server-for-mongodb) - Percona Server for MongoDB® is a free, enhanced, fully compatible, open source, drop-in replacement for the MongoDB® Communi 
ty Edition that includes enterprise-grade features and functionality. 
- **Percona Server for MongoDB** (https://www.percona.com/software/mongo-database/percona-server-for-mongodb) - Percona Server for MongoDB® is a free, enhanced, fully compatible, open source, drop-in replacement for the MongoDB® Community Edition 
 that includes enterprise-grade features and functionality. 
- **MemDB** (https://github.com/rain1017/memdb) - Distributed Transactional In-Memory Database (based on MongoDB). 
 - Elasticsearch (https://www.elastic.co/) - Search & Analyze Data in Real Time.
 - Couchbase (https://www.couchbase.com/) - The highest performing NoSQL distributed database.
@@ -86,8 +87,7 @@
 - Heroic (https://github.com/spotify/heroic) - A scalable time series database based on Cassandra and Elasticsearch, by Spotify.
 - Druid (https://github.com/apache/incubator-druid) - Column oriented distributed data store ideal for powering interactive applications.
 - Riak-TS (https://basho.com/products/riak-ts/) - Riak TS is the only enterprise-grade NoSQL time series database optimized specifically for IoT and Time Series data.
 - Akumuli (https://github.com/akumuli/Akumuli) - Akumuli is a numeric time-series database. It can be used to capture, store and process time-series data in real-time. The word "akumuli" can be translated from esperanto as 
"accumulate".
 - Akumuli (https://github.com/akumuli/Akumuli) - Akumuli is a numeric time-series database. It can be used to capture, store and process time-series data in real-time. The word "akumuli" can be translated from esperanto as "accumulate".
 - Rhombus (https://github.com/Pardot/Rhombus) - A time-series object store for Cassandra that handles all the complexity of building wide row indexes.
 - Dalmatiner DB (https://github.com/dalmatinerdb/dalmatinerdb) - Fast distributed metrics database.
 - Blueflood (https://github.com/rackerlabs/blueflood) - A distributed system designed to ingest and process time series data.
@@ -98,11 +98,12 @@
 - cayley (https://github.com/cayleygraph/cayley) - An open-source graph database. Google.
 - Snappydata (https://github.com/SnappyDataInc/snappydata) - SnappyData: OLTP + OLAP Database built on Apache Spark.
 - TimescaleDB (https://www.timescale.com/) - Built as an extension on top of PostgreSQL, TimescaleDB is a time-series SQL database providing fast analytics, scalability, with automated data management on a proven storage engine.
 - DuckDB (https://duckdb.org/) - DuckDB is a fast in-process analytical database that has zero external dependencies, runs on Linux/macOS/Windows, offers a rich SQL dialect, and is free and extensible.
Data Comparison
- datacompy (https://github.com/capitalone/datacompy) - DataComPy is a Python library that facilitates the comparison of two DataFrames in pandas, Polars, Spark and more. The library goes beyond basic equality checks by providing 
detailed insights into discrepancies at both row and column levels. 
- datacompy (https://github.com/capitalone/datacompy) - DataComPy is a Python library that facilitates the comparison of two DataFrames in pandas, Polars, Spark and more. The library goes beyond basic equality checks by providing detailed 
insights into discrepancies at both row and column levels.
Data Ingestion
@@ -116,21 +117,27 @@
 - kafka-manager (https://github.com/yahoo/kafka-manager) - A tool for managing Apache Kafka.
 - kafka-node (https://github.com/SOHU-Co/kafka-node) - Node.js client for Apache Kafka 0.8.
 - Secor (https://github.com/pinterest/secor) - Pinterest's Kafka to S3 distributed consumer.
 - Kafka-logger (https://github.com/uber/kafka-logger) - Kafka-winston logger for Node.js from uber.
 - Kafka-logger (https://github.com/uber/kafka-logger) - Kafka-winston logger for Node.js from Uber.
- AWS Kinesis (https://aws.amazon.com/kinesis/) - A fully managed, cloud-based service for real-time data processing over large, distributed data streams.
- RabbitMQ (https://www.rabbitmq.com/) - Robust messaging for applications.
- dlt (https://www.dlthub.com) - A fast&simple pipeline building library for python data devs, runs in notebooks, cloud functions, airflow, etc. 
- dlt (https://www.dlthub.com) - A fast&simple pipeline building library for python data devs, runs in notebooks, cloud functions, airflow, etc.
- FluentD (https://www.fluentd.org) - An open source data collector for unified logging layer.
- Embulk (https://www.embulk.org) - An open source bulk data loader that helps data transfer between various databases, storages, file formats, and cloud services.
- Apache Sqoop (https://sqoop.apache.org) - A tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.
- Heka (https://github.com/mozilla-services/heka) - Data Acquisition and Processing Made Easy. Deprecated.
- Gobblin (https://github.com/apache/incubator-gobblin) - Universal data ingestion framework for Hadoop from Linkedin.
- Gobblin (https://github.com/apache/incubator-gobblin) - Universal data ingestion framework for Hadoop from LinkedIn.
- Nakadi (https://nakadi.io) - Nakadi is an open source event messaging platform that provides a REST API on top of Kafka-like queues.
- Pravega (https://www.pravega.io) - Pravega provides a new storage abstraction - a stream - for continuous and unbounded data.
- Apache Pulsar (https://pulsar.apache.org/) - Apache Pulsar is an open-source distributed pub-sub messaging system.
- AWS Data Wranlger (https://github.com/awslabs/aws-data-wrangler) - Utility belt to handle data on AWS.
- AWS Data Wrangler (https://github.com/awslabs/aws-data-wrangler) - Utility belt to handle data on AWS.
- Airbyte (https://airbyte.io/) - Open-source data integration for modern data teams.
- Artie (https://www.artie.com/) - Real-time data ingestion tool leveraging change data capture.
- Sling (https://slingdata.io/) - Sling is CLI data integration tool specialized in moving data between databases, as well as storage systems.
- Meltano (https://meltano.com/) - CLI & code-first ELT.
 - Singer SDK (https://sdk.meltano.com) - The fastest way to build custom data extractors and loaders compliant with the Singer Spec.
- Google Sheets ETL (https://github.com/fulldecent/google-sheets-etl) - Live import all your Google Sheets to your data warehouse.
- CsvPath Framework (https://www.csvpath.org/) - A delimited data preboarding framework that fills the gap between MFT and the data lake.
- Estuary Flow (https://estuary.dev) - No/low-code data pipeline platform that handles both batch and real-time data ingestion.
File System
@@ -139,13 +146,14 @@
- AWS S3 (https://aws.amazon.com/s3/) - Object storage built to retrieve any amount of data from anywhere.
 - smart_open (https://github.com/RaRe-Technologies/smart_open) - Utils for streaming large files (S3, HDFS, gzip, bz2).
- Alluxio (https://www.alluxio.org/) - Alluxio is a memory-centric distributed storage system enabling reliable data sharing at memory-speed across cluster frameworks, such as Spark and MapReduce.
- CEPH (https://ceph.com/) - Ceph is a unified, distributed storage system designed for excellent performance, reliability and scalability.
- CEPH (https://ceph.com/) - Ceph is a unified, distributed storage system designed for excellent performance, reliability, and scalability.
- JuiceFS (https://github.com/juicedata/juicefs) - JuiceFS is a high-performance Cloud-Native file system driven by object storage for large-scale data storage.
- OrangeFS (https://www.orangefs.org/) - Orange File System is a branch of the Parallel Virtual File System.
- SnackFS (https://github.com/tuplejump/snackfs-release) - SnackFS is our bite-sized, lightweight HDFS compatible FileSystem built over Cassandra.
- SnackFS (https://github.com/tuplejump/snackfs-release) - SnackFS is our bite-sized, lightweight HDFS compatible file system built over Cassandra.
- GlusterFS (https://www.gluster.org/) - Gluster Filesystem.
- XtreemFS (https://www.xtreemfs.org/) - Fault-tolerant distributed file system for all storage needs.
- SeaweedFS (https://github.com/chrislusf/seaweedfs) - Seaweed-FS is a simple and highly scalable distributed file system. There are two objectives: to store billions of files! to serve the files fast! Instead of supporting full POSIX 
file system semantics, Seaweed-FS choose to implement only a key~file mapping. Similar to the word "NoSQL", you can call it as "NoFS".
- SeaweedFS (https://github.com/chrislusf/seaweedfs) - Seaweed-FS is a simple and highly scalable distributed file system. There are two objectives: to store billions of files! to serve the files fast! Instead of supporting full POSIX file system
semantics, Seaweed-FS choose to implement only a key~file mapping. Similar to the word "NoSQL", you can call it as "NoFS".
- S3QL (https://github.com/s3ql/s3ql/) - S3QL is a file system that stores all its data online using storage services like Google Storage, Amazon S3, or OpenStack.
- LizardFS (https://lizardfs.com/) - LizardFS Software Defined Storage is a distributed, parallel, scalable, fault-tolerant, Geo-Redundant and highly available file system.
@@ -170,6 +178,7 @@
- Apache Samza (https://samza.apache.org) - Apache Samza is a distributed stream processing framework.
- Apache NiFi (https://nifi.apache.org/) - An easy to use, powerful, and reliable system to process and distribute data.
- Apache Hudi (https://hudi.apache.org/) - An open source framework for managing storage for real time processing, one of the most interesting feature is the Upsert.
- CocoIndex (https://github.com/cocoindex-io/cocoindex) - An open source ETL framework to build fresh index for AI. 
- VoltDB (https://voltdb.com/) - VoltDb is an ACID-compliant RDBMS which uses a shared nothing architecture (https://en.wikipedia.org/wiki/Shared-nothing_architecture).
- PipelineDB (https://github.com/pipelinedb/pipelinedb) - The Streaming SQL Database.
- Spring Cloud Dataflow (https://cloud.spring.io/spring-cloud-dataflow/) - Streaming and tasks execution between Spring Boot apps.
@@ -177,12 +186,13 @@
- Robinhood's Faust (https://github.com/faust-streaming/faust) - Forever scalable event processing & in-memory durable K/V store as a library with asyncio & static typing.
- HStreamDB (https://github.com/hstreamdb/hstream) - The streaming database built for IoT data storage and real-time processing.
- Kuiper (https://github.com/emqx/kuiper) - An edge lightweight IoT data analytics/streaming software implemented by Golang, and it can be run at all kinds of resource-constrained edge devices.
- Zilla (https://github.com/aklivity/zilla) - - An API gateway built for event-driven architectures and streaming that supports standard protocols such as HTTP, SSE, gRPC, MQTT and the native Kafka protocol.
- Zilla (https://github.com/aklivity/zilla) - - An API gateway built for event-driven architectures and streaming that supports standard protocols such as HTTP, SSE, gRPC, MQTT, and the native Kafka protocol.
- SwimOS (https://github.com/swimos/swim-rust) - A framework for building real-time streaming data processing applications that supports a wide range of ingestion sources.
Batch Processing
- Hadoop MapReduce (https://hadoop.apache.org/docs/current/hadoop-mapreduce-client/hadoop-mapreduce-client-core/MapReduceTutorial.html) - Hadoop MapReduce is a software framework for easily writing applications which process vast 
amounts of data (multi-terabyte data-sets) - in-parallel on large clusters (thousands of nodes) - of commodity hardware in a reliable, fault-tolerant manner.
- Hadoop MapReduce (https://hadoop.apache.org/docs/current/hadoop-mapreduce-client/hadoop-mapreduce-client-core/MapReduceTutorial.html) - Hadoop MapReduce is a software framework for easily writing applications which process vast amounts of data 
(multi-terabyte data-sets) - in-parallel on large clusters (thousands of nodes) - of commodity hardware in a reliable, fault-tolerant manner.
- Spark (https://spark.apache.org/) - A multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.
 - Spark Packages (https://spark-packages.org) - A community index of packages for Apache Spark.
 - Deep Spark (https://github.com/Stratio/deep-spark) - Connecting Apache Spark with different data stores. Deprecated.
@@ -192,14 +202,14 @@
- AWS EMR (https://aws.amazon.com/emr/) - A web service that makes it easy to quickly and cost-effectively process vast amounts of data.
- Data Mechanics (https://www.datamechanics.co) - A cloud-based platform deployed on Kubernetes making Apache Spark more developer-friendly and cost-effective.
- Tez (https://tez.apache.org/) - An application framework which allows for a complex directed-acyclic-graph of tasks for processing data.
- Bistro (https://github.com/asavinov/bistro) - A light-weight engine for general-purpose data processing including both batch and stream analytics. It is based on a novel unique data model, which represents data via _functions_ and 
processes data via _columns operations_ as opposed to having only set operations in conventional approaches like MapReduce or SQL.
- Bistro (https://github.com/asavinov/bistro) - A light-weight engine for general-purpose data processing including both batch and stream analytics. It is based on a novel unique data model, which represents data via _functions_ and processes 
data via _columns operations_ as opposed to having only set operations in conventional approaches like MapReduce or SQL.
- Substation (https://github.com/brexhq/substation) - Substation is a cloud native data pipeline and transformation toolkit written in Go.
- Batch ML
 - H2O (https://www.h2o.ai/) - Fast scalable machine learning API for smarter applications.
 - Mahout (https://mahout.apache.org/) - An environment for quickly creating scalable performant machine learning applications.
 - Spark MLlib (https://spark.apache.org/docs/latest/ml-guide.html) - Spark's scalable machine learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative 
filtering, dimensionality reduction, as well as underlying optimization primitives.
 - Spark MLlib (https://spark.apache.org/docs/latest/ml-guide.html) - Spark's scalable machine learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, 
dimensionality reduction, as well as underlying optimization primitives.
- Batch Graph
 - GraphLab Create (https://turi.com/products/create/docs/) - A machine learning platform that enables data scientists and app developers to easily create intelligent apps at scale.
 - Giraph (https://giraph.apache.org/) - An iterative graph processing system built for high scalability.
@@ -217,7 +227,7 @@
- ZingChart (https://www.zingchart.com/) - Fast JavaScript charts for any data set.
- C3.js (https://c3js.org) - D3-based reusable chart library.
- D3.js (https://d3js.org/) - A JavaScript library for manipulating documents based on data.
 - D3Plus (https://d3plus.org) - D3's simplier, easier to use cousin. Mostly predefined templates that you can just plug data in.
 - D3Plus (https://d3plus.org) - D3's simpler, easier to use cousin. Mostly predefined templates that you can just plug data in.
- SmoothieCharts (https://smoothiecharts.org) - A JavaScript Charting Library for Streaming Data.
- PyXley (https://github.com/stitchfix/pyxley) - Python helpers for building dashboards using Flask and React.
- Plotly (https://github.com/plotly/dash) - Flask, JS, and CSS boilerplate for interactive, web-based visualization apps in Python.
@@ -225,45 +235,51 @@
- Redash (https://redash.io/) - Make Your Company Data Driven. Connect to any data source, easily visualize and share your data.
- Metabase (https://github.com/metabase/metabase) - Metabase is the easy, open source way for everyone in your company to ask questions and learn from data.
- PyQtGraph (https://www.pyqtgraph.org/) - PyQtGraph is a pure-python graphics and GUI library built on PyQt4 / PySide and numpy. It is intended for use in mathematics / scientific / engineering applications.
- Seaborn (https://seaborn.pydata.org) - A Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.
Workflow
- Luigi (https://github.com/spotify/luigi) - Luigi is a Python module that helps you build complex pipelines of batch jobs.
 - CronQ (https://github.com/seatgeek/cronq) - An application cron-like system. Used (https://chairnerd.seatgeek.com/building-out-the-seatgeek-data-pipeline/) w/Luige. Deprecated.
- CronQ (https://github.com/seatgeek/cronq) - An application cron-like system. Used (https://chairnerd.seatgeek.com/building-out-the-seatgeek-data-pipeline/) w/Luige. Deprecated.
- Cascading (https://www.cascading.org/) - Java based application development platform.
- Airflow (https://github.com/apache/airflow) - Airflow is a system to programmaticaly author, schedule and monitor data pipelines.
- Azkaban (https://azkaban.github.io/) - Azkaban is a batch workflow job scheduler created at LinkedIn to run Hadoop jobs. Azkaban resolves the ordering through job dependencies and provides an easy to use web user interface to maintain
and track your workflows.
- Airflow (https://github.com/apache/airflow) - Airflow is a system to programmatically author, schedule, and monitor data pipelines.
- Azkaban (https://azkaban.github.io/) - Azkaban is a batch workflow job scheduler created at LinkedIn to run Hadoop jobs. Azkaban resolves the ordering through job dependencies and provides an easy-to-use web user interface to maintain and track
your workflows.
- Oozie (https://oozie.apache.org/) - Oozie is a workflow scheduler system to manage Apache Hadoop jobs.
- Pinball (https://github.com/pinterest/pinball) - DAG based workflow manager. Job flows are defined programmaticaly in Python. Support output passing between jobs.
- Pinball (https://github.com/pinterest/pinball) - DAG based workflow manager. Job flows are defined programmatically in Python. Support output passing between jobs.
- Dagster (https://github.com/dagster-io/dagster) - Dagster is an open-source Python library for building data applications.
- Hamilton (https://github.com/dagworks-inc/hamilton) - Hamilton is a lightweight library to define data transformations as a directed-acyclic graph (DAG). If you like dbt for SQL transforms, you will like Hamilton for Python processing.
- Kedro (https://kedro.readthedocs.io/en/latest/) - Kedro is a framework that makes it easy to build robust and scalable data pipelines by providing uniform project templates, data abstraction, configuration and pipeline assembly.
- Dataform (https://dataform.co/) - An open-source framework and web based IDE to manage datasets and their dependencies. SQLX extends your existing SQL warehouse dialect to add features that support dependency management, testing, 
documentation and more.
- Dataform (https://dataform.co/) - An open-source framework and web based IDE to manage datasets and their dependencies. SQLX extends your existing SQL warehouse dialect to add features that support dependency management, testing, documentation 
and more.
- Census (https://getcensus.com/) - A reverse-ETL tool that let you sync data from your cloud data warehouse to SaaS applications like Salesforce, Marketo, HubSpot, Zendesk, etc. No engineering favors required—just SQL.
- dbt (https://getdbt.com/) - A command line tool that enables data analysts and engineers to transform data in their warehouses more effectively.
- RudderStack (https://github.com/rudderlabs/rudder-server) - A warehouse-first Customer Data Platform that enables you to collect data from every application, website and SaaS platform, and then activate it in your warehouse and 
business tools.
- Kestra (https://kestra.io/) - Scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.
- RudderStack (https://github.com/rudderlabs/rudder-server) - A warehouse-first Customer Data Platform that enables you to collect data from every application, website and SaaS platform, and then activate it in your warehouse and business tools.
- PACE (https://github.com/getstrm/pace) - An open source framework that allows you to enforce agreements on how data should be accessed, used, and transformed, regardless of the data platform (Snowflake, BigQuery, DataBricks, etc.)
- Prefect (https://prefect.io/) - Prefect is an orchestration and observability platform. With it, developers can rapidly build and scale resilient code, and triage disruptions effortlessly.
- Multiwoven (https://github.com/Multiwoven/multiwoven) - The open-source reverse ETL, data activation platform for modern data teams.
- SuprSend (https://www.suprsend.com/products/workflows) - Create automated workflows and logic using API's for your notification service. Add templates, batching, preferences, inapp inbox with workflows to trigger notifications 
directly from your data warehouse.
- SuprSend (https://www.suprsend.com/products/workflows) - Create automated workflows and logic using API's for your notification service. Add templates, batching, preferences, inapp inbox with workflows to trigger notifications directly from 
your data warehouse.
- Kestra (https://github.com/kestra-io/kestra) - A versatile open source orchestrator and scheduler built on Java, designed to handle a broad range of workflows with a language-agnostic, API-first architecture.
- Mage (https://www.mage.ai) - Open-source data pipeline tool for transforming and integrating data.
Data Lake Management
- lakeFS (https://github.com/treeverse/lakeFS) - lakeFS is an open source platform that delivers resilience and manageability to object-storage based data lakes.
- Project Nessie (https://github.com/projectnessie/nessie) - Project Nessie is a Transactional Catalog for Data Lakes with Git-like semantics. Works with Apache Iceberg tables.
- Ilum (https://ilum.cloud/) - Ilum is a modular Data Lakehouse platform that simplifies the management and monitoring of Apache Spark clusters across Kubernetes and Hadoop environments.
- Gravitino (https://github.com/apache/gravitino) - Gravitino is an open-source, unified metadata management for data lakes, data warehouses, and external catalogs. 
ELK Elastic Logstash Kibana
- docker-logstash (https://github.com/pblittle/docker-logstash) - A highly configurable logstash (1.4.4) - docker image running Elasticsearch (1.7.0) - and Kibana (3.1.2).
- docker-logstash (https://github.com/pblittle/docker-logstash) - A highly configurable Logstash (1.4.4) - Docker image running Elasticsearch (1.7.0) - and Kibana (3.1.2).
- elasticsearch-jdbc (https://github.com/jprante/elasticsearch-jdbc) - JDBC importer for Elasticsearch.
- ZomboDB (https://github.com/zombodb/zombodb) - Postgres Extension that allows creating an index backed by Elasticsearch.
Docker
- Gockerize (https://github.com/redbooth/gockerize) - Package golang service into minimal docker containers.
- Gockerize (https://github.com/redbooth/gockerize) - Package golang service into minimal Docker containers.
- Flocker (https://github.com/ClusterHQ/flocker) - Easily manage Docker containers & their data.
- Rancher (https://rancher.com/rancher-os/) - RancherOS is a 20mb Linux distro that runs the entire OS as Docker containers.
- Kontena (https://www.kontena.io/) - Application Containers for Masses.
@@ -272,8 +288,8 @@
- cAdvisor (https://github.com/google/cadvisor) - Analyzes resource usage and performance characteristics of running containers.
- Micro S3 persistence (https://github.com/figadore/micro-s3-persistence) - Docker microservice for saving/restoring volume data to S3.
- Rocker-compose (https://github.com/grammarly/rocker-compose) - Docker composition tool with idempotency features for deploying apps composed of multiple containers. Deprecated.
- Nomad (https://github.com/hashicorp/nomad) - Nomad is a cluster manager, designed for both long lived services and short lived batch processing workloads.
- ImageLayers (https://imagelayers.io/) - Vizualize docker images and the layers that compose them.
- Nomad (https://github.com/hashicorp/nomad) - Nomad is a cluster manager, designed for both long-lived services and short-lived batch processing workloads.
- ImageLayers (https://imagelayers.io/) - Visualize Docker images and the layers that compose them.
Datasets
@@ -287,7 +303,7 @@
- GitHub Archive (https://www.gharchive.org/) - GitHub's public timeline since 2011, updated every hour.
- Common Crawl (https://commoncrawl.org/) - Open source repository of web crawl data.
- Wikipedia (https://dumps.wikimedia.org/enwiki/latest/) - Wikipedia's complete copy of all wikis, in the form of wikitext source and metadata embedded in XML. A number of raw database tables in SQL form are also available.
- Wikipedia (https://dumps.wikimedia.org/enwiki/latest/) - Wikipedia's complete copy of all wikis, in the form of Wikitext source and metadata embedded in XML. A number of raw database tables in SQL form are also available.
Monitoring
@@ -304,15 +320,17 @@
Testing
- Grai (https://github.com/grai-io/grai-core/) - A data catalog tool that integrates into your CI system exposing downstream impact testing of data changes. These tests prevent data changes which might break data pipelines or BI 
dashboards from making it to production.
- Grai (https://github.com/grai-io/grai-core/) - A data catalog tool that integrates into your CI system exposing downstream impact testing of data changes. These tests prevent data changes which might break data pipelines or BI dashboards from 
making it to production.
- DQOps (https://github.com/dqops/dqo) - An open-source data quality platform for the whole data platform lifecycle from profiling new data sources to applying full automation of data quality monitoring.
- DataKitchen (https://datakitchen.io/) - Open Source Data Observability for end-to-end Data Journey Observability, data profiling, anomaly detection, and auto-created data quality validation tests.
- RunSQL (https://runsql.com/) - Free online SQL playground for MySQL, PostgreSQL, and SQL Server. Create database structures, run queries, and share results instantly.
Community
Forums
- /r/dataengineering (https://www.reddit.com/r/dataengineering/) - News, tips and background on Data Engineering.
- /r/dataengineering (https://www.reddit.com/r/dataengineering/) - News, tips, and background on Data Engineering.
- /r/etl (https://www.reddit.com/r/ETL/) - Subreddit focused on ETL.
Conferences
@@ -322,5 +340,13 @@
Podcasts
- Data Engineering Podcast (https://www.dataengineeringpodcast.com/) - The show about modern data infrastructure.
- The Data Stack Show (https://datastackshow.com/) - A show where they talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, 
and driving better outcomes across their businesses with data.
- The Data Stack Show (https://datastackshow.com/) - A show where they talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and 
driving better outcomes across their businesses with data.
Books
- Snowflake Data Engineering (https://www.manning.com/books/snowflake-data-engineering) - A practical introduction to data engineering on the Snowflake cloud data platform.
- Best Data Science Books (https://www.appliedaicourse.com/blog/data-science-books/) - This blog offers a curated list of top data science books, categorized by topics and learning stages, to aid readers in building foundational knowledge and 
staying updated with industry trends.
dataengineering Github: https://github.com/igorbarinov/awesome-data-engineering