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DBMS > Apache Impala vs. GridDB vs. H2GIS vs. Realm vs. Warp 10

System Properties Comparison Apache Impala vs. GridDB vs. H2GIS vs. Realm vs. Warp 10

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonH2GIS  Xexclude from comparisonRealm  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataSpatial extension of H2A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSTime Series DBMSSpatial DBMSDocument storeTime Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#383  Overall
#7  Spatial DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websiteimpala.apache.orggriddb.netwww.h2gis.orgrealm.iowww.warp10.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.netwww.h2gis.org/­docs/­homerealm.io/­docswww.warp10.io/­content/­02_Getting_started
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationCNRSRealm, acquired by MongoDB in May 2019SenX
Initial release20132013201320142015
Current release4.1.0, June 20225.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoLGPL 3.0Open SourceOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++JavaJava
Server operating systemsLinuxLinuxAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes
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.nonononono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)yesnono
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP API
Jupyter
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infobased on H2no inforuns within the applications so server-side scripts are unnecessaryyes infoWarpScript
Triggersnoyesyesyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenoneSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes infobased on H2noneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infoIn-Memory realmyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseyes infobased on H2yesMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
Apache ImpalaGridDBH2GISRealmWarp 10
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Apache ImpalaGridDBH2GISRealmWarp 10
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