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DBMS > Apache Pinot vs. CrateDB vs. Drizzle vs. FileMaker

System Properties Comparison Apache Pinot vs. CrateDB vs. Drizzle vs. FileMaker

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonCrateDB  Xexclude from comparisonDrizzle  Xexclude from comparisonFileMaker  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.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyDistributed 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.
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score48.20
Rank#20  Overall
#14  Relational DBMS
Websitepinot.apache.orgcratedb.comwww.claris.com/­filemaker
Technical documentationdocs.pinot.apache.orgcratedb.com/­docswww.claris.com/­resources/­documentation
DeveloperApache Software Foundation and contributorsCrateDrizzle project, originally started by Brian AkerClaris infoa subsidiary of Apple
Initial release2015201320081983
Current release1.0.0, September 20237.2.4, September 201219.4.1, November 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoGNU GPLcommercial
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 languageJavaJavaC++
Server operating systemsAll OS with a Java JDK11 or higherAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
OS X
iOS infoclient part only
Linux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
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 format
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilityyes infowith proprietary extensionsyes infovia plugins
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBCFilemaker WebDirect
JDBC
ODBC
Supported programming languagesGo
Java
Python
.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
PHP
Server-side scripts infoStored proceduresuser defined functions (Javascript)noyes
Triggersnono infohooks for callbacks inside the server can be used.yes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingnone
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 14
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integritynoyesyes
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 strategyACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlrights management via user accountsPluggable authentication mechanisms infoe.g. LDAP, HTTPsimple rights management via user accounts and connection to external directory services
More information provided by the system vendor
Apache PinotCrateDBDrizzleFileMaker
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache PinotCrateDBDrizzleFileMaker
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