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DBMS > Kdb vs. RavenDB vs. Spark SQL vs. Stardog

System Properties Comparison Kdb vs. RavenDB vs. Spark SQL vs. Stardog

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Editorial information provided by DB-Engines
NameKdb  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionHigh performance Time Series DBMSOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelTime Series DBMS
Vector DBMS
Document storeRelational DBMSGraph DBMS
RDF store
Secondary database modelsRelational DBMSGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitekx.comravendb.netspark.apache.org/­sqlwww.stardog.com
Technical documentationcode.kx.comravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperKx Systems, a division of First Derivatives plcHibernating RhinosApache Software FoundationStardog-Union
Initial release2000 infokdb was released 2000, kdb+ in 2003201020142010
Current release3.6, May 20185.4, July 20223.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open Sourcecommercial infofree 32-bit versionOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageqC#ScalaJava
Server operating systemsLinux
OS X
Solaris
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeyesschema-freeyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesnoyesyes
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.yesnono infoImport/export of XML data possible
Secondary indexesyes infotable attribute 'grouped'yesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like query language (q)SQL-like query language (RQL)SQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsyesnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes infowith viewsyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infosimilar paradigm used for internal processingyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesnonoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, Cluster-wide transaction availablenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlrights management via user accountsAuthorization levels configured per client per databasenoAccess rights for users and roles
More information provided by the system vendor
KdbRavenDBSpark SQLStardog
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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KdbRavenDBSpark SQLStardog
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