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DBMS > Apache Impala vs. EJDB vs. Faircom EDGE vs. Microsoft Azure Synapse Analytics vs. openGemini

System Properties Comparison Apache Impala vs. EJDB vs. Faircom EDGE vs. Microsoft Azure Synapse Analytics vs. openGemini

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEJDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonopenGemini  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 environmentsElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerAn open source distributed Time Series DBMS with high concurrency, high performance, and high scalability
Primary database modelRelational DBMSDocument storeKey-value store
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.31
Rank#296  Overall
#44  Document stores
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.09
Rank#361  Overall
#37  Time Series DBMS
Websiteimpala.apache.orggithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-edgeazure.microsoft.com/­services/­synapse-analyticswww.opengemini.org
github.com/­openGemini
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.microsoft.com/­azure/­synapse-analyticsdocs.opengemini.org/­guide
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSoftmotionsFairCom CorporationMicrosoftHuawei and openGemini community
Initial release20132012197920162022
Current release4.1.0, June 2022V3, October 20201.1, July 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPLv2commercial infoRestricted, free version availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CANSI C, C++C++Go
Server operating systemsLinuxserver-lessAndroid
Linux infoARM, x86
Raspbian
Windows
hostedLinux
Windows
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyes, ANSI Standard SQL TypesyesInteger, Float, Boolean, String
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.noyesnono
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoANSI SQL queriesyesSQL-like 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
ADO.NET
JDBC
ODBC
HTTP REST
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#
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes info.Net, JavaScript, C/C++Transact SQLno
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneFile partitioning infoCustomizable business rules for partitioningSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneyes infoSynchronous and asynchronous realtime replication based on transaction logsyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possibleyes infowhen using SQLno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyes infoacross SQL and NoSQLyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
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.yesAdministrators and common users accounts

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More resources
Apache ImpalaEJDBFaircom EDGE infoformerly c-treeEDGEMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseopenGemini
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