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DBMS > CrateDB vs. Kdb vs. Newts vs. SAP HANA

System Properties Comparison CrateDB vs. Kdb vs. Newts vs. SAP HANA

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonKdb  Xexclude from comparisonNewts  Xexclude from comparisonSAP HANA  Xexclude from comparison
DescriptionDistributed Database based on LuceneHigh performance Time Series DBMSTime Series DBMS based on CassandraIn-memory, column based data store. Available as appliance or cloud service
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMS
Vector DBMS
Time Series DBMSRelational DBMS
Secondary database modelsRelational DBMSRelational DBMSDocument store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial 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
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score44.69
Rank#22  Overall
#16  Relational DBMS
Websitecratedb.comkx.comopennms.github.io/­newtswww.sap.com/­products/­hana.html
Technical documentationcratedb.com/­docscode.kx.comgithub.com/­OpenNMS/­newts/­wikihelp.sap.com/­hana
DeveloperCrateKx Systems, a division of First Derivatives plcOpenNMS GroupSAP
Initial release20132000 infokdb was released 2000, kdb+ in 200320142010
Current release3.6, May 20182.0 SPS07 (April 4, 2023), April 2023
License infoCommercial or Open SourceOpen Sourcecommercial infofree 32-bit versionOpen Source infoApache 2.0commercial
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 languageJavaqJava
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Appliance or cloud-service
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
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.noyesnono
Secondary indexesyesyes infotable attribute 'grouped'noyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query language (q)noyes
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
HTTP REST
Java 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
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Java
Server-side scripts infoStored proceduresuser defined functions (Javascript)user defined functionsnoSQLScript, R
Triggersnoyes infowith viewsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infobased on Cassandrayes
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replicationselectable replication factor infobased on Cassandrayes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infosimilar paradigm used for internal processingnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
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 strategynonoACID
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.noyesnoyes
User concepts infoAccess controlrights management via user accountsrights management via user accountsnoyes
More information provided by the system vendor
CrateDBKdbNewtsSAP HANA
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
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Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
tick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
kdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more
upon request
» more

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CrateDBKdbNewtsSAP HANA
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