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DBMS > Elasticsearch vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. Oracle Coherence vs. Quasardb

System Properties Comparison Elasticsearch vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. Oracle Coherence vs. Quasardb

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Coherence  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFully managed big data interactive analytics platformOracles in-memory data grid solutionDistributed, high-performance timeseries database
Primary database modelSearch engineKey-value store
Relational DBMS
Relational DBMS infocolumn orientedKey-value storeTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document 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
Score135.35
Rank#7  Overall
#1  Search engines
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.92
Rank#130  Overall
#22  Key-value stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitewww.elastic.co/­elasticsearchwww.faircom.com/­products/­faircom-edgeazure.microsoft.com/­services/­data-explorerwww.oracle.com/­java/­coherencequasar.ai
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­middleware/­standalone/­coherencedoc.quasar.ai/­master
DeveloperElasticFairCom CorporationMicrosoftOraclequasardb
Initial release20101979201920072009
Current release8.6, January 2023V3, October 2020cloud service with continuous releases14.1, August 20233.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoElastic Licensecommercial infoRestricted, free version availablecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaANSI C, C++JavaC++
Server operating systemsAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
hostedAll OS with a Java VMBSD
Linux
OS X
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentFlexible Schema (defined schema, partial schema, schema free)Fixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes infointeger and binary
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.noyesyesnono
Secondary indexesyes infoAll search fields are automatically indexedyesall fields are automatically indexednoyes infowith tags
SQL infoSupport of SQLSQL-like query languageyes infoANSI SQL queriesKusto Query Language (KQL), SQL subsetnoSQL-like query language
APIs and other access methodsJava API
RESTful HTTP/JSON API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JCache
JPA
RESTful HTTP API
HTTP API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Java
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, Rnono
Triggersyes infoby using the 'percolation' featureyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoLive Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningSharding infoImplicit feature of the cloud serviceShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with selectable consistency levelSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectornoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoconfigurableACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infooptionallyyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationyesnoyesyes infoTransient mode
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Azure Active Directory Authenticationauthentification to access the cache via certificates or http basic authenticationCryptographically strong user authentication and audit trail

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More resources
ElasticsearchFaircom EDGE infoformerly c-treeEDGEMicrosoft Azure Data ExplorerOracle CoherenceQuasardb
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