For an open source data warehouse for analytics, the strongest matches are druid-io/druid (Druid is a distributed, columnar analytical database designed for), citusdata/citus (Citus is a distributed SQL engine that scales PostgreSQL) and apache/doris (Doris is a high-performance distributed SQL data warehouse and). clickhouse/clickhouse and starrocks/starrocks round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
Selectăm repository-uri open-source de pe GitHub care se potrivesc cu „open source alternatives to snowflake”. Rezultatele sunt clasificate după relevanța față de căutarea ta — folosește filtrele de mai jos pentru a rafina rezultatele sau utilizează AI-ul.
Druid is a distributed columnar store and online analytical processing database designed for real-time analytics. It functions as a SQL analytics platform and a streaming data ingestion engine, allowing for the analysis of large datasets with low latency to support interactive dashboards and high-concurrency operational workloads. The system integrates a streaming data ingestion engine that loads information via batch or streaming processes to enable immediate analysis of arriving data. It provides high-performance analytical processing to execute slice-and-dice queries on massive data volume
Druid is a distributed, columnar analytical database designed for high-concurrency SQL queries and real-time data ingestion, making it a flagship platform for large-scale data warehousing and lakehouse workloads.
Citus is a PostgreSQL extension that transforms a standard database into a distributed system. It functions as a sharding framework and distributed SQL engine, enabling horizontal scaling by partitioning tables across a cluster of nodes. By utilizing a coordinator-worker topology, the system manages metadata and routes queries to the appropriate nodes, allowing for parallel execution of complex operations across distributed data shards. The platform distinguishes itself through its specialized support for multi-tenant architectures and real-time analytical processing. It enables tenant-based
Citus is a distributed SQL engine that scales PostgreSQL horizontally through sharding and parallel query execution, making it a capable platform for large-scale analytical workloads despite being an extension rather than a standalone data lakehouse.
Doris is a distributed SQL data warehouse designed for high-performance analytical workloads and real-time data processing. It functions as a unified platform that integrates traditional relational warehousing with lakehouse query capabilities, allowing users to execute analytical operations directly against external data lakes without requiring data migration. The system distinguishes itself through a shared-nothing, massively parallel processing architecture that utilizes vectorized query execution and columnar storage to maintain sub-second latency. It supports dynamic schema evolution, en
Doris is a high-performance distributed SQL data warehouse and lakehouse platform that features columnar storage, horizontal scalability, and native support for querying external data lakes, directly matching the requirements for large-scale analytical workloads.
ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale data aggregation. It functions as a distributed data warehouse capable of processing petabytes of information, while also providing an embedded engine that integrates directly into applications for native query capabilities without external dependencies. The system is built to handle high-throughput ingestion and complex analytical workloads, delivering millisecond-level latency for interactive dashboards and operational monitoring. The platform distinguishes itself through ad
ClickHouse is a high-performance, distributed columnar database designed specifically for large-scale analytical SQL queries, offering the horizontal scalability and storage flexibility required for a modern data lakehouse architecture.
StarRocks is a distributed SQL OLAP database engine designed for real-time analytics and high-performance multi-dimensional analysis. It functions as a data lakehouse query engine that enables SQL execution across large datasets and external open table formats without requiring local data imports. The system employs a shared-nothing distributed architecture and utilizes the MySQL protocol to integrate with business intelligence tools. It maintains real-time data consistency through a primary key upsert model and accelerates query response times using vectorized execution and cost-based optimi
StarRocks is a high-performance distributed SQL engine that functions as a data lakehouse platform, supporting horizontal scaling, columnar storage, and direct querying of S3-compatible data lake formats.
Kylin is a distributed OLAP engine designed for executing fast SQL queries on massive datasets. It utilizes multi-dimensional data cubes to pre-calculate data aggregates, enabling sub-second response times for large-scale analytical queries and big data analytics. The system focuses on large-scale data warehousing and multi-dimensional data modeling. It allows for the organization and querying of vast amounts of structured data to support business intelligence and reporting workflows through distributed SQL querying.
Kylin is a distributed OLAP engine that provides a SQL-based interface for large-scale analytical queries, though it relies on pre-calculated data cubes rather than the direct lakehouse storage patterns typical of modern data warehouses.
Apache Hive is a SQL-on-Hadoop data warehouse that enables querying and managing petabytes of data stored in distributed storage such as HDFS and cloud storage services. It provides a familiar SQL interface for batch analytics and reporting, supported by a core set of components including the HiveServer2 Thrift service for remote query execution, the Hive Metastore Service for central metadata management, the Hive ACID Transaction Engine for concurrent read-write operations, and the Hive LLAP Interactive Engine for low-latency analytical processing. The WebHCat REST API offers an HTTP interfac
Apache Hive is a mature distributed data warehouse platform that provides a SQL-based analytical engine, columnar storage support, and horizontal scalability over distributed storage, making it a foundational tool for large-scale data lakehouse architectures.
OceanBase is a distributed SQL database designed for high availability and strong consistency across multiple nodes and regions. It functions as a hybrid transactional and analytical processing engine, allowing real-time analytics and transactions to execute on a single data copy. The system also serves as a vector database engine for indexing and querying vector data to power semantic search and recommendation systems. The platform features native compatibility layers for MySQL and Oracle, enabling the migration of legacy workloads without rewriting SQL code. It utilizes a Paxos-based distri
OceanBase is a distributed HTAP database that supports large-scale analytical SQL queries and columnar storage, making it a capable platform for analytical workloads despite its primary focus on hybrid transactional processing.
Trino is a distributed SQL query engine designed for large-scale data analytics. It functions as a data federation platform, providing a unified interface that allows users to execute complex analytical queries across multiple heterogeneous data sources simultaneously without requiring data movement or transformation. The engine utilizes a massively parallel processing architecture to scale compute resources across clusters for high-speed data retrieval. It distinguishes itself through a cost-based query optimizer that analyzes metadata to determine efficient execution plans, alongside dynami
Trino is a high-performance distributed SQL query engine that provides the analytical compute layer for data lakehouses, though it functions as a query engine rather than a full-stack storage and compute platform.
Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer
Pinot is a distributed, columnar OLAP database designed for high-concurrency analytical queries, making it a strong fit for large-scale data warehousing needs despite its primary focus on real-time, user-facing analytics rather than traditional batch-heavy lakehouse workloads.
YDB is a distributed SQL database and analytical engine designed for horizontal scalability and strong consistency. It functions as a multi-model system that supports transactional and analytical workloads through a distributed architecture providing serializable ACID transactions. The system is distinguished by its broad protocol compatibility, implementing the PostgreSQL wire protocol for standard SQL drivers and the Kafka protocol for messaging and streaming. It further serves as a vector database, supporting vector indexes and approximate nearest neighbor searches for semantic search and
YDB is a distributed SQL database that supports both transactional and analytical workloads with horizontal scalability and columnar storage capabilities, making it a viable platform for large-scale analytical queries.
TiDB is a horizontally scalable, distributed SQL database designed to provide consistent transactional storage and high-performance analytical processing within a single unified architecture. It utilizes a decoupled compute-storage design and a distributed key-value storage layer to ensure horizontal scalability and efficient range-based queries. By employing a consensus-based replication algorithm, the system maintains high availability and automatic failover across multiple nodes and geographical regions. The platform distinguishes itself through its hybrid transactional and analytical proc
TiDB is a distributed HTAP database that provides the horizontal scalability and SQL-based analytical processing required for large-scale data workloads, though it is primarily architected as a NewSQL database rather than a dedicated data lakehouse.
Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing
Presto is a distributed SQL query engine that provides the analytical processing and horizontal scalability required for a data lakehouse, though it functions as a query layer rather than a full-stack storage platform.
| Repository | Stele | Limbaj | Licență | Ultimul push |
|---|---|---|---|---|
| druid-io/druid | 14K | Java | Apache-2.0 | |
| citusdata/citus | 12.6K | C | AGPL-3.0 | |
| apache/doris | 15.5K | Java | Apache-2.0 | |
| clickhouse/clickhouse | 48.2K | C++ | Apache-2.0 | |
| starrocks/starrocks | 11.8K | Java | Apache-2.0 | |
| apache/kylin | 3.8K | Java | Apache-2.0 | |
| apache/hive | 6K | Java | apache-2.0 | |
| oceanbase/oceanbase | 10K | C++ | other | |
| trinodb/trino | 13K | Java | Apache-2.0 | |
| apache/pinot | 6.1K | Java | Apache-2.0 |