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DBMS > Datomic vs. HEAVY.AI vs. Spark SQL vs. TimescaleDB vs. Transbase

System Properties Comparison Datomic vs. HEAVY.AI vs. Spark SQL vs. TimescaleDB vs. Transbase

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTransbase  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 hardwareSpark SQL is a component on top of 'Spark Core' for structured data processingA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.datomic.comgithub.com/­heavyai/­heavydb
www.heavy.ai
spark.apache.org/­sqlwww.timescale.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.datomic.comdocs.heavy.aispark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCognitectHEAVY.AI, Inc.Apache Software FoundationTimescaleTransaction Software GmbH
Initial release20122016201420171987
Current release1.0.7075, December 20235.10, January 20223.5.0 ( 2.13), September 20232.15.0, May 2024Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0Open Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++ and CUDAScalaCC and C++
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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 indexesyesnonoyesyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Thrift
Vega
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
Java
All languages supporting JDBC/ODBC/Thrift
Python
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
TriggersBy using transaction functionsnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoRound robinyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replicationnoneSource-replica replication with hot standby and reads on replicas infoSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDyes
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 developmentyesnonono
User concepts infoAccess controlnofine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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