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DBMS > Datomic vs. HEAVY.AI vs. Kinetica vs. Solr vs. SwayDB

System Properties Comparison Datomic vs. HEAVY.AI vs. Kinetica vs. Solr vs. SwayDB

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonSolr  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsA widely used distributed, scalable search engine based on Apache LuceneAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engineKey-value store
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitewww.datomic.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comsolr.apache.orgswaydb.simer.au
Technical documentationdocs.datomic.comdocs.heavy.aidocs.kinetica.comsolr.apache.org/­resources.html
DeveloperCognitectHEAVY.AI, Inc.KineticaApache Software FoundationSimer Plaha
Initial release20122016201220062018
Current release1.0.6735, June 20235.10, January 20227.1, August 20219.6.0, April 2024
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache Version 2Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++ and CUDAC, C++JavaScala
Server operating systemsAll OS with a Java VMLinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typingno
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.nononoyesno
Secondary indexesyesnoyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSolr Parallel SQL Interfaceno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnouser defined functionsJava pluginsno
TriggersBy using transaction functionsnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoRound robinShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replicationSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonooptimistic lockingAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
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 developmentyesyes infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users and roles on table levelyesno

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More resources
DatomicHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaSolrSwayDB
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