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DBMS > Apache Impala vs. Graph Engine vs. GridDB vs. Informix

System Properties Comparison Apache Impala vs. Graph Engine vs. GridDB vs. Informix

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonGridDB  Xexclude from comparisonInformix  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineScalable in-memory time series database optimized for IoT and Big DataA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data
Primary database modelRelational DBMSGraph DBMS
Key-value store
Time Series DBMSRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDB
Secondary database modelsDocument storeKey-value store
Relational DBMS
Document store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score17.87
Rank#35  Overall
#22  Relational DBMS
Websiteimpala.apache.orgwww.graphengine.iogriddb.netwww.ibm.com/­products/­informix
Technical documentationimpala.apache.org/­impala-docs.htmlwww.graphengine.io/­docs/­manualdocs.griddb.netinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftToshiba CorporationIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.
Initial release2013201020131984
Current release4.1.0, June 20225.1, August 202214.10.FC5, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMIT LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++.NET and CC++C, C++ and Java
Server operating systemsLinux.NETLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes infoSince Version 12.10 support for JSON/BSON datatypes
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
F#
Visual Basic
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnoyes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingSharding
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 containersImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseUsers with fine-grained authentication, authorization, and auditing controls
More information provided by the system vendor
Apache ImpalaGraph Engine infoformer name: TrinityGridDBInformix
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 ImpalaGraph Engine infoformer name: TrinityGridDBInformix
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