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DBMS > Datomic vs. Dragonfly vs. Spark SQL vs. TimescaleDB vs. Transbase

System Properties Comparison Datomic vs. Dragonfly vs. Spark SQL vs. TimescaleDB vs. Transbase

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDragonfly  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 drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceSpark 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 DBMSKey-value storeRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.49
Rank#261  Overall
#38  Key-value stores
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/­dragonflydb/­dragonfly
www.dragonflydb.io
spark.apache.org/­sqlwww.timescale.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.datomic.comwww.dragonflydb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCognitectDragonflyDB team and community contributorsApache Software FoundationTimescaleTransaction Software GmbH
Initial release20122023201420171987
Current release1.0.6735, June 20231.0, March 20233.5.0 ( 2.13), September 20232.15.0, May 2024Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoBSL 1.1Open 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++ScalaCC and C++
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesscheme-freeyesyesyes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyesnumerics, 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 SQLnonoSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsRESTful HTTP APIProprietary protocol infoRESP - REdis Serialization ProtocolJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
Java
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
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 FunctionsLuanouser 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 functionspublish/subscribe channels provide some trigger functionalitynoyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyes, 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 peersSource-replica 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 ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of command blocks and scriptsnoACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyesyes
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 controlnoPassword-based authenticationnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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DatomicDragonflySpark SQLTimescaleDBTransbase
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