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DBMS > Apache Impala vs. GridDB vs. OrientDB vs. Stardog

System Properties Comparison Apache Impala vs. GridDB vs. OrientDB vs. Stardog

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonOrientDB  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataMulti-model DBMS (Document, Graph, Key/Value)Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSTime Series DBMSDocument store
Graph DBMS
Key-value store
Graph DBMS
RDF store
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
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websiteimpala.apache.orggriddb.netorientdb.orgwww.stardog.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.netwww.orientdb.com/­docs/­last/­index.htmldocs.stardog.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationOrientDB LTD; CallidusCloud; SAPStardog-Union
Initial release2013201320102010
Current release4.1.0, June 20225.1, August 20223.2.29, March 20247.3.0, May 2020
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 infoApache version 2commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++JavaJava
Server operating systemsLinuxLinuxAll OS with a Java JDK (>= JDK 6)Linux
macOS
Windows
Data schemeyesyesschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")schema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.nononono infoImport/export of XML data possible
Secondary indexesyesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language, no joinsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava, Javascriptuser defined functions and aggregates, HTTP Server extensions in Java
TriggersnoyesHooksyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replicationMulti-source replication in HA-Cluster
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 infocould be achieved with distributed queriesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynonoyes inforelationship in graphsyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseAccess rights for users and roles; record level security configurableAccess rights for users and roles
More information provided by the system vendor
Apache ImpalaGridDBOrientDBStardog
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 ImpalaGridDBOrientDBStardog
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