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DBMS > GeoSpock vs. GridGain vs. Hawkular Metrics

System Properties Comparison GeoSpock vs. GridGain vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonGridGain  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
DescriptionSpatial and temporal data processing engine for extreme data scaleGridGain is an in-memory computing platform, built on Apache IgniteHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#299  Overall
#138  Relational DBMS
Score2.06
Rank#125  Overall
#25  Key-value stores
#61  Relational DBMS
Score0.02
Rank#340  Overall
#30  Time Series DBMS
Websitegeospock.comwww.gridgain.comwww.hawkular.org
Technical documentationdocs.geospock.com/­Content/­Home.htmwww.gridgain.com/­docs/­latestwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperGeoSpockGridGain Systems, Inc.Community supported by Red Hat
Initial release20072014
Current release2.0, September 2019GridGain 8.5.1
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptJava, C++, .NetJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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 indexestemporal, categoricalyesno
SQL infoSupport of SQLANSI SQL for query only (using Presto)ANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBCHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP REST
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes (cache interceptors and events)yes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)selectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users can be defined per tableSecurity Hooks for custom implementationsno

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More resources
GeoSpockGridGainHawkular Metrics
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How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

Cambridge-Based GeoSpock Secures £10 Million Additional Funding
8 January 2019, Business Wire

Cambridge-based data analytics startup GeoSpock lands €4.6 million
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UK-based database GeoSpock bags $5.4m, to expand into
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