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DBMS > KairosDB vs. Netezza vs. Solr vs. Sqrrl vs. Yanza

System Properties Comparison KairosDB vs. Netezza vs. Solr vs. Sqrrl vs. Yanza

Editorial information provided by DB-Engines
NameKairosDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSolr  Xexclude from comparisonSqrrl  Xexclude from comparisonYanza  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.Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDistributed Time Series DBMS based on Cassandra or H2Data warehouse and analytics appliance part of IBM PureSystemsA widely used distributed, scalable search engine based on Apache LuceneAdaptable, secure NoSQL built on Apache AccumuloTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSRelational DBMSSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Time Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.62
Rank#239  Overall
#20  Time Series DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitegithub.com/­kairosdb/­kairosdbwww.ibm.com/­products/­netezzasolr.apache.orgsqrrl.comyanza.com
Technical documentationkairosdb.github.iosolr.apache.org/­resources.html
DeveloperIBMApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.Yanza
Initial release20132000200620122015
Current release1.2.2, November 20189.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2commercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava
Server operating systemsLinux
OS X
Windows
Linux infoincluded in applianceAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)LinuxWindows
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyesno
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.noyesno
Secondary indexesnoyesyes infoAll search fields are automatically indexedyesno
SQL infoSupport of SQLnoyesSolr Parallel SQL Interfacenono
APIs and other access methodsGraphite protocol
HTTP REST
Telnet API
JDBC
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
HTTP API
Supported programming languagesJava
JavaScript infoNode.js
PHP
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
any language that supports HTTP calls
Server-side scripts infoStored proceduresnoyesJava pluginsnono
Triggersnonoyes infoUser configurable commands triggered on index changesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingShardingSharding infomaking use of Hadoopnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationyesselectable replication factor infomaking use of Hadoopnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingAtomic updates per row, document, or graph entityno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlsimple password-based access controlUsers with fine-grained authorization conceptyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)no

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More resources
KairosDBNetezza infoAlso called PureData System for Analytics by IBMSolrSqrrlYanza
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