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DBMS > CrateDB vs. Drizzle vs. FileMaker vs. KairosDB

System Properties Comparison CrateDB vs. Drizzle vs. FileMaker vs. KairosDB

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonDrizzle  Xexclude from comparisonFileMaker  Xexclude from comparisonKairosDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionDistributed Database based on LuceneMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.FileMaker is a cross-platform RDBMS that includes a GUI frontend.Distributed Time Series DBMS based on Cassandra or H2
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#9  Vector DBMS
Score47.91
Rank#20  Overall
#14  Relational DBMS
Score0.67
Rank#233  Overall
#20  Time Series DBMS
Websitecratedb.comwww.claris.com/­filemakergithub.com/­kairosdb/­kairosdb
Technical documentationcratedb.com/­docswww.claris.com/­resources/­documentationkairosdb.github.io
DeveloperCrateDrizzle project, originally started by Brian AkerClaris infoa subsidiary of Apple
Initial release2013200819832013
Current release7.2.4, September 201219.4.1, November 20211.2.2, November 2018
License infoCommercial or Open SourceOpen SourceOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0
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.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaC++Java
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
OS X
iOS infoclient part only
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infoA http query request can return the data in XML formatno
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyes infowith proprietary extensionsyes infovia pluginsno
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBCFilemaker WebDirect
JDBC
ODBC
Graphite protocol
HTTP REST
Telnet API
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C++
Java
PHP
PHPJava
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)noyesno
Triggersnono infohooks for callbacks inside the server can be used.yesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replication
Source-replica replication
Source-replica replication, warm standby infosince Version 14selectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDnono
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.nono
User concepts infoAccess controlrights management via user accountsPluggable authentication mechanisms infoe.g. LDAP, HTTPsimple rights management via user accounts and connection to external directory servicessimple password-based access control
More information provided by the system vendor
CrateDBDrizzleFileMakerKairosDB
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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CrateDBDrizzleFileMakerKairosDB
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