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DBMS > Apache Impala vs. GridDB vs. VoltDB

System Properties Comparison Apache Impala vs. GridDB vs. VoltDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonVoltDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument storeKey-value store
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
Score1.44
Rank#158  Overall
#73  Relational DBMS
Websiteimpala.apache.orggriddb.netwww.voltdb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.netdocs.voltdb.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationVoltDB Inc.
Initial release201320132010
Current release4.1.0, June 20225.1, August 202211.3, April 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 infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java, C++
Server operating systemsLinuxLinuxLinux
OS X infofor development
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)yes infoonly a subset of SQL 99
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication
Source-replica replication
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 jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynonono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseUsers and roles with access to stored procedures
More information provided by the system vendor
Apache ImpalaGridDBVoltDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache ImpalaGridDBVoltDB
Recent citations in the news

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6 June 2023, SiliconANGLE News

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

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Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ...
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Unveiling Volt Active Data's game-changing approach to limitless app performance
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 VoltDB Launches Active(N) Lossless Cross Data Center Replication
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VoltDB Turns to Real-Time Analytics with NewSQL Database
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VoltDB Upgrades Power, Security of Its In-Memory Database
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29 January 2015, ADT Magazine

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