RavenDB
| Original author | Oren Eini (aka Ayende Rahien) |
|---|---|
| Developer | RavenDB[1] |
| Release | 2010 |
| Stable release | 7.2 LTS / February 2026 |
| Written in | C# |
| Engine | Voron |
| Operating system | Windows, Linux, Mac OS, AWS, Azure, GCP |
| Available in | English |
| Type | Document-oriented database |
| License | AGPLv3 |
| Website | ravendb.net |
| Repository | github.com/ravendb/ravendb |
RavenDB is an open-source document-oriented database written in C#, developed by RavenDB Ltd.[2][3][1][4] It's built on top of the custom Voron storage engine and supports ACID transactions. RavenDB uses a SQL-like query language, (RQL), and includes native features for handling time series, graph querying, and full-text search. It is cross-platform, supported on Windows, Linux, Mac OS, AWS, Azure, and GCP and can be deployed on cloud, on-prem, and the edge, including constrained environments such as Raspberry Pi Zero.[5] RavenDB can be deployed in distributed clusters with master-master replication.
History#edit
Originally named "Rhino DivanDB",[6] RavenDB began in 2008 as a project by Oren Eini (aka Ayende Rahien)[7][8] and was developed by the company’s former name, Hibernating Rhinos Ltd.[1] RavenDB is described as one of the first document databases to run natively on the .NET Framework, and to offer multi-document ACID transactions[2][3][9][10][11][12]
In 2019, the company began offering RavenDB as a cloud service named RavenDB Cloud.[13][14][15]
In 2020, version 5.0 added document compression and time series support.[16][17] Subsequent releases included version 5.2 (LTS) in 2021 with improvements for business intelligence and ETL workflows,[18][19] version 6.0 in 2023 with a new indexing engine, sharding support, and messaging‑queue integrations,[20][21] and version 6.2 (LTS) in 2024 with further stability and operational enhancements.[22]
In February 2025, version 7 was released with vector search and AI integration.[23]
In July 2025, version 7.1 introduced AI Agent Creator and GenAI Integration.[24]
In August 2025, the company officially changed its name from “Hibernating Rhinos Ltd.” to “RavenDB Ltd.”[25]
In February 2026, version 7.2 was announced as an LTS release.[26]
Background#edit
RavenDB was created primarily for the .NET ecosystem and was one of the early document databases to provide full ACID transactions. Over time, it has expanded from a .NET-centric document database into a cross-platform product with client APIs for multiple runtimes and deployment options on-premises and in the cloud. Its feature set has advanced and now includes cluster-wide transactions, full-text search based on Lucene and Corax (full text search engines), time series support, ETL and analytics integrations. Additionally, starting with version 7.x, the following AI related features are available: vector search capabilities intended for AI and semantic search workloads, generative AI and AI Agents features. As of 2025, RavenDB serves over 12,000 customers and over 1,000 organizations.
Version history#edit
| Version | Date | Features added (partial list) |
|---|---|---|
| 7.2 | February 2026[27] | Native AI Assistant, Remote Attachments, and JSON Schema Validation |
| 7.1 | June 2025[28] | Generative AI integration; AI Agents; Embedding Generation[29] |
| 7.0 | February 2025[30] | Vector Search; ETL for Amazon SQS and Snowflake[31] |
| 6.2 | Sept 2024[32] | ETL to Azure Queue Storage; Open Telemetry support |
| 6.0 | August 2023[33] | Corax; Sharding; Data Archival; Sinks for Kafka and RabbitMQ |
| 5.4 | June 2022[34] | Corax experimental release; ETL for Kafka and RabbitMQ[35] |
| 5.3 | November 2021[36] | Concurrent Data Subscriptions;[37] Microsoft Power BI support[38] |
| 5.2 | June 2021[39] | OLAP ETL;[40] Custom Analyzers[41] |
| 5.1 | November 2020[42] | Indexing attachments;[43] Hub/Sink replication with filtering[44] |
| 5.0 | July 2020 | Time series;[45] Data compression using the Zstd algorithm[46] |
| 4.2 | May 2019[47] | Graph querying[48] |
| 4.1 | August 2018[49] | Cluster-wide transactions[48][50] |
| 4.0 | February 2018[51] | Became cross-platform; free license[52] |
| 3.5 | October 2016[53] | Clustering[54] |
| 3.0 | November 2014[55] | Java API; Voron storage engine[56][57] |
| 2.5 | June 2013[58] | Projections; facet querying |
| 2.0 | January 2013[59] | Replication[60] |
| 1.0 | May 2010[61] |
- Green: Supported
- Red: Not supported
System architecture#edit
Data is stored as schemaless documents blittable format that allows fast transformations from and to JSON.[2][4][6][62][63] Documents are grouped into collections, with each document having exactly one collection.[64]
Databases can be deployed on a distributed cluster of servers (called ‘nodes’) using multi-master replication.[3] RavenDB uses a custom implementation of Raft called Rachis for consensus and clustering. Replication is performed in a cluster-agnostic manner. Tasks are distributed to the different nodes in a balanced way.[65]
Versions 1.0 through 3.5 supported sharding, but versions 4.x do not,[2][3] and reintroduced sharding starting with version 6.0.[66]
RavenDB originally used the ESENT storage engine.[6][7] Version 3.0 replaced it with a new open-source storage engine called Voron. Since 5.4, RavenDB provides a custom-built indexing engine called Corax.[67][68][69]
Hub/Sink replication with filtering is available since 5.1, and sharding is supported starting from 6.0.[70]
Clients are supported for C#, C++, Java, NodeJS, Python, Ruby, PHP and Go.[3]
Main features#edit
- ACID transactions, including cluster-wide
- Clustering with Raft consensus[65]
- An efficient custom storage engine[6][7][8]
- Asynchronous indexing[71][72]
- Automatic indexing[73]
Indexes and querying#edit
Queries are expressed in LINQ or with a custom query language named RQL (stands for Raven Query Language) with syntax similar to SQL.[2][3]
- Auto indexes - in RavenDB queries can only be satisfied by an index; if no appropriate index exists, a new index is created to satisfy the query.[4][10][74]
- Projection - indexes can be configured to transform indexed data, perform calculations, perform aggregations, and execute JavaScript code on the server side.[3][75]
- Full-text search - at a low level, data is indexed with Lucene.net or Corax, which means indexes support full-text search.[12][76][77]
- Vector search - documents can be searched by their semantic similarity; they are indexed using HNSW algorithm; RavenDB supports embeddings generation.
Document extensions#edit
Documents can be extended with other data types less suited to JSON. These extensions can be loaded, modified, and stored independently of the document itself.[78]
- Attachments - documents can have multiple attachments of any data type, such as images, audio, or pure binary.[79]
- Time Series - numerical data associated with specific times and ordered chronologically.[80][81]
- Distributed counters - atomic counters that can be modified concurrently across the cluster without locking or conflicts.[82]
- Revisions - a built-in audit capability, capturing snapshots of documents as they change; revisions can be used for data auditing, instant restoration after document corruption, and other purposes.[83]
Cluster-wide ACID Transactions#edit
ACID transactions can be executed at the scope of a cluster (in addition to single node transactions). The transaction will only be persisted if it is confirmed by a consensus of nodes; if it is not, the transaction is cancelled and rolled back.[48]
Generative AI and Vector Integration#edit
In version 7.1, RavenDB introduced a comprehensive AI integration layer, positioning the database as a core component for Retrieval-Augmented Generation (RAG) and other AI workflows, eliminating the need for external vector databases.
- Vector Database Capabilities: RavenDB natively stores and indexes high-dimensional embedding vectors, enabling searches based on contextual similarity rather than exact keywords.[84]
- Generative AI Tasks: This feature allows for autonomous, intelligent data processing by defining ongoing tasks that run within the database.[85]
- AI Agents: RavenDB AI Agents facilitate continuous, interactive conversations between a client and an LLM, leveraging the database's data. The conversation history is stored within the database, allowing for multi-turn interactions.[86]
RavenDB Cloud#edit
Embedded instance#edit
RavenDB can also be run as an embedded instance, a great option for smaller applications and proof of concepts, for instance..[87]
Licensing#edit
Security and reliability#edit
RavenDB implements authentication and authorization using X.509 certificates. Client certificates are associated with security clearances and database-level permissions, and all communications can be encrypted using TLS/SSL or HTTPS. The database also supports auditing of operations to track access and changes.[89]
For disaster recovery, RavenDB provides ongoing backup tasks, including full and incremental backups, which allow point-in-time recovery. Replication tasks can maintain live copies of data and synchronize it across multiple regions.[90]
RavenDB tracks and assesses publicly reported vulnerabilities. For example, CVE‑2025‑55315 was publicly triaged and analyzed through the vendor’s official channels.[91]
References#edit
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- ^ a b c d e f g "RavenDB System Properties". db-engines.com. Retrieved 10 October 2020.
- ^ a b c Kaur, Harpreet, and Kamal Jeet Kaur. "A Review: Study of Document oriented databases and their Security." International Journal of Advanced Research in Computer Science 4.8 (2013).
- ^ Wallen, Jack (2021-01-06). "How to create a new database with RavenDB". TechRepublic. Retrieved 2022-11-22.
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- ^ "RavenDB: Driving DX through DB infrastructure management". ciostory.com. Archived from the original on 11 October 2020. Retrieved 10 October 2020.
- ^ "RavenDB 5 Improves Distributed Time-Series, Document Compression, and Indexing". infoq.com. Aug 3, 2020. Retrieved 10 October 2020.
- ^ "RavenDB Adds Time Series Query Support". i-programmer.info. 16 July 2020. Retrieved 10 October 2020.
- ^ "How can I implement an atomic concurrent read of a document in RavenDB?". Stack Overflow. Retrieved 2025-11-27.
- ^ "Viewing Document Revisions | RavenDB Documentation". docs.ravendb.net. Retrieved 2025-11-27.
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- ^ "GenAI tasks: Start | RavenDB Documentation". docs.ravendb.net. Retrieved 2025-11-27.
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- ^ "Server: Running an Embedded Instance | RavenDB Documentation". docs.ravendb.net. Retrieved 2025-11-27.
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External links#edit
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