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DBMS > Datomic vs. Quasardb vs. Riak TS vs. Spark SQL

System Properties Comparison Datomic vs. Quasardb vs. Riak TS vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonQuasardb  Xexclude from comparisonRiak TS  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityDistributed, high-performance timeseries databaseRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score0.28
Rank#307  Overall
#27  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.comquasar.aispark.apache.org/­sql
Technical documentationdocs.datomic.comdoc.quasar.ai/­masterwww.tiot.jp/­riak-docs/­riak/­ts/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectquasardbOpen Source, formerly Basho TechnologiesApache Software Foundation
Initial release2012200920152014
Current release1.0.7075, December 20233.14.1, January 20243.0.0, September 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++ErlangScala
Server operating systemsAll OS with a Java VMBSD
Linux
OS X
Windows
Linux
OS X
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infointeger and binarynoyes
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.nononono
Secondary indexesyesyes infowith tagsrestrictedno
SQL infoSupport of SQLnoSQL-like query languageyes, limitedSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIHTTP APIHTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesClojure
Java
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoErlangno
TriggersBy using transaction functionsnoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoconsistent hashingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replication with selectable replication factorselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infolinks between datasets can be storedno
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)yes infoby using LevelDByesyes
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 infoTransient modeno
User concepts infoAccess controlnoCryptographically strong user authentication and audit trailnono

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DatomicQuasardbRiak TSSpark SQL
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