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DBMS > Blueflood vs. CrateDB vs. Kinetica vs. SAP HANA

System Properties Comparison Blueflood vs. CrateDB vs. Kinetica vs. SAP HANA

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonCrateDB  Xexclude from comparisonKinetica  Xexclude from comparisonSAP HANA  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraDistributed Database based on LuceneFully vectorized database across both GPUs and CPUsIn-memory, column based data store. Available as appliance or cloud service
Primary database modelTime Series DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMS
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
Document store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial 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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score44.69
Rank#22  Overall
#16  Relational DBMS
Websiteblueflood.iocratedb.comwww.kinetica.comwww.sap.com/­products/­hana.html
Technical documentationgithub.com/­rax-maas/­blueflood/­wikicratedb.com/­docsdocs.kinetica.comhelp.sap.com/­hana
DeveloperRackspaceCrateKineticaSAP
Initial release2013201320122010
Current release7.1, August 20212.0 SPS07 (April 4, 2023), April 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono infoalso available as a cloud based service
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++
Server operating systemsLinux
OS X
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxAppliance or cloud-service
Data schemepredefined schemeFlexible 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.nononono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like DML and DDL statementsyes
APIs and other access methodsHTTP RESTADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
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++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions (Javascript)user defined functionsSQLScript, R
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingShardingyes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraConfigurable replication on table/partition-levelSource-replica replicationyes
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 or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
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 strategynoACID
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.nonoyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlnorights management via user accountsAccess rights for users and roles on table levelyes
More information provided by the system vendor
BluefloodCrateDBKineticaSAP HANA
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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BluefloodCrateDBKineticaSAP HANA
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