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

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

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDuckDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAn embeddable, in-process, column-oriented SQL OLAP RDBMSA 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 Lucene
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSSearch engine
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
Score4.57
Rank#74  Overall
#40  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
Websitewww.datomic.comduckdb.orggithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comsolr.apache.org
Technical documentationdocs.datomic.comduckdb.org/­docsdocs.heavy.aidocs.kinetica.comsolr.apache.org/­resources.html
DeveloperCognitectHEAVY.AI, Inc.KineticaApache Software Foundation
Initial release20122018201620122006
Current release1.0.6735, June 20230.10, February 20245.10, January 20227.1, August 20219.6.0, April 2024
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoMIT LicenseOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache Version 2
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++C++ and CUDAC, C++Java
Server operating systemsAll OS with a Java VMserver-lessLinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyesyes infosupports customizable data types and automatic typing
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.nonononoyes
Secondary indexesyesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyesyesSQL-like DML and DDL statementsSolr Parallel SQL Interface
APIs and other access methodsRESTful HTTP APIArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
C
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
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
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonouser defined functionsJava plugins
TriggersBy using transaction functionsnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneSharding infoRound robinShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneMulti-source replicationSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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 developmentyesyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standardAccess rights for users and roles on table levelyes

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More resources
DatomicDuckDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaSolr
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