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DBMS > Faircom EDGE vs. Hazelcast vs. Hive vs. JSqlDb vs. Microsoft Azure Data Explorer

System Properties Comparison Faircom EDGE vs. Hazelcast vs. Hive vs. JSqlDb vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHazelcast  Xexclude from comparisonHive  Xexclude from comparisonJSqlDb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA widely adopted in-memory data griddata warehouse software for querying and managing large distributed datasets, built on HadoopJavaScript Query Language Database, stores JavaScript objects and primitivesFully managed big data interactive analytics platform
Primary database modelKey-value store
Relational DBMS
Key-value storeRelational DBMSDocument store
Object oriented DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document 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
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.faircom.com/­products/­faircom-edgehazelcast.comhive.apache.orgjsqldb.org (offline)azure.microsoft.com/­services/­data-explorer
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhazelcast.org/­imdg/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperFairCom CorporationHazelcastApache Software Foundation infoinitially developed by FacebookKonrad von BackstromMicrosoft
Initial release19792008201220182019
Current releaseV3, October 20205.3.6, November 20233.1.3, April 20220.8, December 2018cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2Open Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++JavaJava
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VMAll OS with a Java VMLinux
macOS
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyesyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.yesyes infothe object must implement a serialization strategynoyes
Secondary indexesyesyesyesnoall fields are automatically indexed
SQL infoSupport of SQLyes infoANSI SQL queriesSQL-like query languageSQL-like DML and DDL statementsnoKusto Query Language (KQL), SQL subset
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
PHP
Python
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infoEvent Listeners, Executor Servicesyes infouser defined functions and integration of map-reducefunctions in JavaScriptYes, possible languages: KQL, Python, R
Triggersyesyes infoEventsnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningShardingShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoReplicated Mapselectable replication factornoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReducenoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infousing RocksDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Role-based access controlAccess rights for users, groups and rolesAzure Active Directory Authentication

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More resources
Faircom EDGE infoformerly c-treeEDGEHazelcastHiveJSqlDbMicrosoft Azure Data Explorer
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