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DBMS > Apache Impala vs. Greenplum vs. GridDB vs. LevelDB vs. RDF4J

System Properties Comparison Apache Impala vs. Greenplum vs. GridDB vs. LevelDB vs. RDF4J

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGreenplum  Xexclude from comparisonGridDB  Xexclude from comparisonLevelDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Scalable in-memory time series database optimized for IoT and Big DataEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSRelational DBMSTime Series DBMSKey-value storeRDF store
Secondary database modelsDocument storeDocument store
Spatial DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteimpala.apache.orggreenplum.orggriddb.netgithub.com/­google/­leveldbrdf4j.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.greenplum.orgdocs.griddb.netgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdrdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPivotal Software Inc.Toshiba CorporationGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20132005201320112004
Current release4.1.0, June 20227.0.0, September 20235.1, August 20221.23, February 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoBSDOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++Java
Server operating systemsLinuxLinuxLinuxIllumos
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeyesyesyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampnoyes
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.noyes infosince Version 4.2nono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL92, SQL-like TQL (Toshiba Query Language)nono
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesAll languages supporting JDBC/ODBCC
Java
Perl
Python
R
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnonoyes
Triggersnoyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes infoin-memory storage is supported as well
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 Kerberosfine grained access rights according to SQL-standardAccess rights for users can be defined per databasenono
More information provided by the system vendor
Apache ImpalaGreenplumGridDBLevelDBRDF4J infoformerly known as Sesame
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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Apache ImpalaGreenplumGridDBLevelDBRDF4J infoformerly known as Sesame
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