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DBMS > Datomic vs. Hypertable vs. RavenDB vs. Weaviate

System Properties Comparison Datomic vs. Hypertable vs. RavenDB vs. Weaviate

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHypertable  Xexclude from comparisonRavenDB  Xexclude from comparisonWeaviate  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAn open source BigTable implementation based on distributed file systems such as HadoopOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSWide column storeDocument storeVector DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.datomic.comravendb.netgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.datomic.comravendb.net/­docsweaviate.io/­developers/­weaviate
DeveloperCognitectHypertable Inc.Hibernating RhinosWeaviate B.V.
Initial release2012200920102019
Current release1.0.6735, June 20230.9.8.11, March 20165.4, July 20221.19, May 2023
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoGNU version 3. Commercial license availableOpen Source infoAGPL version 3, commercial license availableOpen 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.
Implementation languageJava, ClojureC++C#Go
Server operating systemsAll OS with a Java VMLinux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeschema-freeyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesnonoyes 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.nono
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLnonoSQL-like query language (RQL)GraphQL is used as query language
APIs and other access methodsRESTful HTTP APIC++ API
Thrift
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
C++
Java
Perl
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyesno
TriggersBy using transaction functionsnoyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factor on file system levelMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyes
User concepts infoAccess controlnonoAuthorization levels configured per client per databaseAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
DatomicHypertableRavenDBWeaviate
Specific characteristicsWeaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesFlexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
» more
Key customersAll companies that have data. ​
» more
Market metricsAs of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsWeaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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DatomicHypertableRavenDBWeaviate
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