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DBMS > EJDB vs. Faircom EDGE vs. Hive vs. Microsoft Azure Data Explorer vs. OrientDB

System Properties Comparison EJDB vs. Faircom EDGE vs. Hive vs. Microsoft Azure Data Explorer vs. OrientDB

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrientDB  Xexclude from comparison
DescriptionEmbeddable 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 environmentsdata warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platformMulti-model DBMS (Document, Graph, Key/Value)
Primary database modelDocument storeKey-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#297  Overall
#44  Document stores
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Websitegithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-edgehive.apache.orgazure.microsoft.com/­services/­data-explorerorientdb.org
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorerwww.orientdb.com/­docs/­last/­index.html
DeveloperSoftmotionsFairCom CorporationApache Software Foundation infoinitially developed by FacebookMicrosoftOrientDB LTD; CallidusCloud; SAP
Initial release20121979201220192010
Current releaseV3, October 20203.1.3, April 2022cloud service with continuous releases3.2.29, March 2024
License infoCommercial or Open SourceOpen Source infoGPLv2commercial infoRestricted, free version availableOpen Source infoApache Version 2commercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCANSI C, C++JavaJava
Server operating systemsserver-lessAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VMhostedAll OS with a Java JDK (>= JDK 6)
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesFixed schema with schema-less datatypes (dynamic)schema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyes, ANSI Standard SQL Typesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.yesyesno
Secondary indexesnoyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoyes infoANSI SQL queriesSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetSQL-like query language, no joins
APIs and other access methodsin-process shared libraryADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
Supported programming languagesActionscript
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
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, RJava, Javascript
Triggersnoyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyHooks
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning infoCustomizable business rules for partitioningShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocould be achieved with distributed queries
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyes infowhen using SQLnonoyes inforelationship in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyes infoacross SQL and NoSQLyesyesyes
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.yesno
User concepts infoAccess controlnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and rolesAzure Active Directory AuthenticationAccess rights for users and roles; record level security configurable

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EJDBFaircom EDGE infoformerly c-treeEDGEHiveMicrosoft Azure Data ExplorerOrientDB
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