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DBMS > Apache Impala vs. EJDB vs. Faircom EDGE vs. GridDB

System Properties Comparison Apache Impala vs. EJDB vs. Faircom EDGE vs. GridDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEJDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEmbeddable document-store database library with JSON representation of queries (in MongoDB style)FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsScalable in-memory time series database optimized for IoT and Big Data
Primary database modelRelational DBMSDocument storeKey-value store
Relational DBMS
Time Series 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
Score0.27
Rank#297  Overall
#44  Document stores
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websiteimpala.apache.orggithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-edgegriddb.net
Technical documentationimpala.apache.org/­impala-docs.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.griddb.net
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSoftmotionsFairCom CorporationToshiba Corporation
Initial release2013201219792013
Current release4.1.0, June 2022V3, October 20205.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPLv2commercial infoRestricted, free version availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CANSI C, C++C++
Server operating systemsLinuxserver-lessAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyes, ANSI Standard SQL Typesyes infonumerical, string, blob, geometry, boolean, timestamp
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.noyesno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoANSI SQL queriesSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
ODBC
in-process shared libraryADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes info.Net, JavaScript, C/C++no
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneyes infoSynchronous and asynchronous realtime replication based on transaction logsSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Tunable Consistency
Immediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possibleyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyes infoacross SQL and NoSQLyes
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 KerberosnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users can be defined per database
More information provided by the system vendor
Apache ImpalaEJDBFaircom EDGE infoformerly c-treeEDGEGridDB
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 ImpalaEJDBFaircom EDGE infoformerly c-treeEDGEGridDB
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