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DBMS > CrateDB vs. GeoSpock vs. Netezza vs. SAP Adaptive Server

System Properties Comparison CrateDB vs. GeoSpock vs. Netezza vs. SAP Adaptive Server

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonGeoSpock  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSAP Adaptive Server infoformer name: Sybase ASE  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionDistributed Database based on LuceneSpatial and temporal data processing engine for extreme data scaleData warehouse and analytics appliance part of IBM PureSystemsThe SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMSTime Series DBMSSpatial DBMS infowith Boeing's Spatial Query Server
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
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score36.31
Rank#25  Overall
#17  Relational DBMS
Websitecratedb.comgeospock.comwww.ibm.com/­products/­netezzawww.sap.com/­products/­technology-platform/­sybase-ase.html
Technical documentationcratedb.com/­docshelp.sap.com/­docs/­SAP_ASE
DeveloperCrateGeoSpockIBMSAP, Sybase
Initial release201320001987
Current release2.0, September 201916.0
License infoCommercial or Open SourceOpen Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
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 languageJavaJava, JavascriptC and C++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedLinux infoincluded in applianceAIX
HP-UX
Linux
Solaris
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
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.nonono
Secondary indexesyestemporal, categoricalyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityANSI SQL for query only (using Presto)yesyes
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBCJDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
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++
Fortran
Java
Lua
Perl
Python
R
C
C++
Cobol
Java
Java
Perl
PHP
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)noyesJava and Transact-SQL
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replicationMulti-source replication
Source-replica replication
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
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
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 strategynoACIDACID
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.nono
User concepts infoAccess controlrights management via user accountsAccess rights for users can be defined per tableUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard
More information provided by the system vendor
CrateDBGeoSpockNetezza infoAlso called PureData System for Analytics by IBMSAP Adaptive Server infoformer name: Sybase ASE
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
CrateDBGeoSpockNetezza infoAlso called PureData System for Analytics by IBMSAP Adaptive Server infoformer name: Sybase ASE
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