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DBMS > Faircom EDGE vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. RocksDB

System Properties Comparison Faircom EDGE vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. RocksDB

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonRocksDB  Xexclude from comparison
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 gridFully managed big data interactive analytics platformDatabase as a Service offering with high compatibility to Microsoft SQL ServerEmbeddable persistent key-value store optimized for fast storage (flash and RAM)
Primary database modelKey-value store
Relational DBMS
Key-value storeRelational DBMS infocolumn orientedRelational DBMSKey-value store
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
Document store
Graph DBMS
Spatial DBMS
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
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score3.65
Rank#85  Overall
#11  Key-value stores
Websitewww.faircom.com/­products/­faircom-edgehazelcast.comazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­products/­azure-sql/­databaserocksdb.org
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­en-us/­azure/­azure-sqlgithub.com/­facebook/­rocksdb/­wiki
DeveloperFairCom CorporationHazelcastMicrosoftMicrosoftFacebook, Inc.
Initial release19792008201920102013
Current releaseV3, October 20205.3.6, November 2023cloud service with continuous releasesV128.11.4, April 2024
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++JavaC++C++
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VMhostedhostedLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeFixed schema with schema-less datatypes (dynamic)yesschema-free
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesno
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 strategyyesyesno
Secondary indexesyesyesall fields are automatically indexedyesno
SQL infoSupport of SQLyes infoANSI SQL queriesSQL-like query languageKusto Query Language (KQL), SQL subsetyesno
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
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
C++ API
Java API
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, RTransact SQLno
Triggersyesyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with always 3 replicas availableyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednoACIDyes
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyesyes
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.yesyesnoyes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Role-based access controlAzure Active Directory Authenticationfine grained access rights according to SQL-standardno

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More resources
Faircom EDGE infoformerly c-treeEDGEHazelcastMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzureRocksDB
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