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DBMS > Datomic vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. Weaviate

System Properties Comparison Datomic vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. Weaviate

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSphinx  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen source search engine for searching in data from different sources, e.g. relational databasesAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSRelational DBMSSearch engineVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score22.71
Rank#30  Overall
#18  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score1.89
Rank#138  Overall
#4  Vector DBMS
Websitewww.datomic.comazure.microsoft.com/­services/­synapse-analyticssphinxsearch.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.datomic.comdocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docsweaviate.io/­developers/­weaviate
DeveloperCognitectMicrosoftSphinx Technologies Inc.Weaviate B.V.
Initial release2012201620012019
Current release1.0.6735, June 20233.5.1, February 20231.19, May 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
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 VMhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesnoyes 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 indexesyesyesyes infofull-text index on all search fieldsyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLnoyesSQL-like query language (SphinxQL)GraphQL is used as query language
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
Proprietary protocolGraphQL query language
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
C#
Java
PHP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyes infoTransaction FunctionsTransact SQLnono
TriggersBy using transaction functionsnonono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
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)yesyes infoThe original contents of fields are not stored in the Sphinx index.yes
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 controlnoyesnoAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
DatomicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinxWeaviate
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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DatomicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinxWeaviate
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