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DBMS > CrateDB vs. Firebird vs. Splunk vs. Yanza

System Properties Comparison CrateDB vs. Firebird vs. Splunk vs. Yanza

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonFirebird  Xexclude from comparisonSplunk  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDistributed Database based on LuceneFirebird is an open source RDBMS forked from Borland's InterBaseAnalytics Platform for Big DataTime Series DBMS for IoT Applications
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSSearch engineTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score20.82
Rank#30  Overall
#18  Relational DBMS
Score86.45
Rank#14  Overall
#2  Search engines
Websitecratedb.comwww.firebirdsql.orgwww.splunk.comyanza.com
Technical documentationcratedb.com/­docswww.firebirdsql.org/­en/­reference-manualsdocs.splunk.com/­Documentation/­Splunk
DeveloperCrateFirebird FoundationSplunk Inc.Yanza
Initial release20132000 infoAs fork of Borland's InterBase20032015
Current release5.0.0, January 2024
License infoCommercial or Open SourceOpen SourceOpen Source infoInitial Developer's Public Licensecommercial infoLimited free edition and free developer edition availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono 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.
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 and C++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
Linux
OS X
Solaris
Windows
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesyesno
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesno infoSplunk Search Processing Language for search commandsno
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
HTTP RESTHTTP 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#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
C#
Java
JavaScript
PHP
Python
Ruby
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functions (Javascript)PSQLyesno
Triggersnoyesyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replicationMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
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 infoA 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searchingno
Concurrency infoSupport for concurrent manipulation of datayesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyes
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 accountsUsers with fine-grained authorization conceptAccess rights for users and rolesno
More information provided by the system vendor
CrateDBFirebirdSplunkYanza
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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CrateDBFirebirdSplunkYanza
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