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DBMS > HEAVY.AI vs. Milvus vs. SurrealDB vs. Weaviate

System Properties Comparison HEAVY.AI vs. Milvus vs. SurrealDB vs. Weaviate

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMilvus  Xexclude from comparisonSurrealDB  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA DBMS designed for efficient storage of vector data and vector similarity searchesA fully ACID transactional, developer-friendly, multi-model DBMSAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSVector DBMSDocument store
Graph DBMS
Vector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
milvus.iosurrealdb.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.heavy.aimilvus.io/­docs/­overview.mdsurrealdb.com/­docsweaviate.io/­developers/­weaviate
DeveloperHEAVY.AI, Inc.SurrealDB LtdWeaviate B.V.
Initial release2016201920222019
Current release5.10, January 20222.3.4, January 2024v1.5.0, May 20241.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache Version 2.0Open SourceOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++ and CUDAC++, GoRustGo
Server operating systemsLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Windows
Data schemeyesschema-freeyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesyes infostring, int, float, geo point, date, cross reference, fuzzy references
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesnonoyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLyesnoSQL-like query languageGraphQL is used as query language
APIs and other access methodsJDBC
ODBC
Thrift
Vega
RESTful HTTP APIGraphQL
RESTful HTTP API
WebSocket
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Go
Java
JavaScript (Node.js)
Python
Deno
Go
JavaScript (Node.js)
Rust
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole based access control and fine grained access rightsyes, based on authentication and database rulesAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022MilvusSurrealDBWeaviate
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
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As a database supporting the development of generative AI and semantic search applications...
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Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
All companies that have data. ​
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
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As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more
Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022MilvusSurrealDBWeaviate
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Recent citations in the news

Big Data Analytics: A Game Changer for Infrastructure
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HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

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