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DBMS > Apache Impala vs. GeoSpock vs. GridGain

System Properties Comparison Apache Impala vs. GeoSpock vs. GridGain

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGeoSpock  Xexclude from comparisonGridGain  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopSpatial and temporal data processing engine for extreme data scaleGridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Websiteimpala.apache.orggeospock.comwww.gridgain.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.gridgain.com/­docs/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGeoSpockGridGain Systems, Inc.
Initial release20132007
Current release4.1.0, June 20222.0, September 2019GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, JavascriptJava, C++, .Net
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
Data schemeyesyesyes
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.nonoyes
Secondary indexesyestemporal, categoricalyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for query only (using Presto)ANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBC
ODBC
JDBCHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes (compute grid and cache interceptors can be used instead)
Triggersnonoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per tableSecurity Hooks for custom implementations

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More resources
Apache ImpalaGeoSpockGridGain
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