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DBMS > Blueflood vs. CrateDB vs. Cubrid vs. Sphinx

System Properties Comparison Blueflood vs. CrateDB vs. Cubrid vs. Sphinx

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonCrateDB  Xexclude from comparisonCubrid  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraDistributed Database based on LuceneCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSSearch engine
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteblueflood.iocratedb.comcubrid.com (korean)
cubrid.org (english)
sphinxsearch.com
Technical documentationgithub.com/­rax-maas/­blueflood/­wikicratedb.com/­docscubrid.org/­manualssphinxsearch.com/­docs
DeveloperRackspaceCrateCUBRID Corporation, CUBRID FoundationSphinx Technologies Inc.
Initial release2013201320082001
Current release11.0, January 20213.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open SourceOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence available
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, C++, JavaC++
Server operating systemsLinux
OS X
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemepredefined schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
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.nonono
Secondary indexesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilityyesSQL-like query language (SphinxQL)
APIs and other access methodsHTTP RESTADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Proprietary protocol
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++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnouser defined functions (Javascript)Java Stored Proceduresno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraConfigurable replication on table/partition-levelSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnorights management via user accountsfine grained access rights according to SQL-standardno
More information provided by the system vendor
BluefloodCrateDBCubridSphinx
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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More resources
BluefloodCrateDBCubridSphinx
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