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DBMS > Kdb vs. Solr vs. Spark SQL vs. Sqrrl

System Properties Comparison Kdb vs. Solr vs. Spark SQL vs. Sqrrl

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Editorial information provided by DB-Engines
NameKdb  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionHigh performance Time Series DBMSA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processingAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelTime Series DBMS
Vector DBMS
Search engineRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsRelational DBMSSpatial 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
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitekx.comsolr.apache.orgspark.apache.org/­sqlsqrrl.com
Technical documentationcode.kx.comsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKx Systems, a division of First Derivatives plcApache Software FoundationApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release2000 infokdb was released 2000, kdb+ in 2003200620142012
Current release3.6, May 20189.6.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree 32-bit versionOpen Source infoApache Version 2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageqJavaScalaJava
Server operating systemsLinux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Linux
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-free
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyesyes
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.yesyesno
Secondary indexesyes infotable attribute 'grouped'yes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLSQL-like query language (q)Solr Parallel SQL InterfaceSQL-like DML and DDL statementsno
APIs and other access methodsHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresuser defined functionsJava pluginsnono
Triggersyes infowith viewsyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark CoreSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infosimilar paradigm used for internal processingspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnoAtomic updates per row, document, or graph entity
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.yesyesno
User concepts infoAccess controlrights management via user accountsyesnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
KdbSolrSpark SQLSqrrl
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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KdbSolrSpark SQLSqrrl
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