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DBMS > ArcadeDB vs. Kinetica vs. PouchDB vs. Rockset vs. Spark SQL

System Properties Comparison ArcadeDB vs. Kinetica vs. PouchDB vs. Rockset vs. Spark SQL

Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonKinetica  Xexclude from comparisonPouchDB  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenFully vectorized database across both GPUs and CPUsJavaScript DBMS with an API inspired by CouchDBA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Relational DBMSDocument storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#366  Overall
#50  Document stores
#38  Graph DBMS
#53  Key-value stores
#36  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score0.79
Rank#211  Overall
#35  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitearcadedb.comwww.kinetica.compouchdb.comrockset.comspark.apache.org/­sql
Technical documentationdocs.arcadedb.comdocs.kinetica.compouchdb.com/­guidesdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperArcade DataKineticaApache Software FoundationRocksetApache Software Foundation
Initial release20212012201220192014
Current releaseSeptember 20217.1, August 20217.1.1, June 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen SourcecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++JavaScriptC++Scala
Server operating systemsAll OS with a Java VMLinuxserver-less, requires a JavaScript environment (browser, Node.js)hostedLinux
OS X
Windows
Data schemeschema-freeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnodynamic typingyes
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 infoingestion from XML files supportedno
Secondary indexesyesyesyes infovia viewsall fields are automatically indexedno
SQL infoSupport of SQLSQL-like query language, no joinsSQL-like DML and DDL statementsnoRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
HTTP RESTJDBC
ODBC
Supported programming languagesJavaC++
Java
JavaScript (Node.js)
Python
JavaScriptGo
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsView functions in JavaScriptnono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infowith a proxy-based framework, named couchdb-loungeAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes inforelationship in graphsyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlAccess rights for users and roles on table levelnoAccess rights for users and organizations can be defined via Rockset consoleno

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More resources
ArcadeDBKineticaPouchDBRocksetSpark SQL
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