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DBMS > Alibaba Cloud Table Store vs. Elasticsearch vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. Sphinx

System Properties Comparison Alibaba Cloud Table Store vs. Elasticsearch vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. Sphinx

Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonElasticsearch  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA fully managed Wide Column Store for large quantities of semi-structured data with real-time accessA 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 metricHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelWide column storeSearch engineDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMS infocolumn orientedSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Graph DBMS
Search engine
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
Score0.26
Rank#301  Overall
#12  Wide column stores
Score135.35
Rank#7  Overall
#1  Search engines
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.alibabacloud.com/­product/­table-storewww.elastic.co/­elasticsearchwww.gigaspaces.comazure.microsoft.com/­services/­data-explorersphinxsearch.com
Technical documentationwww.alibabacloud.com/­help/­en/­tablestorewww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.gigaspaces.com/­latest/­landing.htmldocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
DeveloperAlibabaElasticGigaspaces TechnologiesMicrosoftSphinx Technologies Inc.
Initial release20162010200020192001
Current release8.6, January 202315.5, September 2020cloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicenseOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetC++
Server operating systemshostedAll OS with a Java VMLinux
macOS
Solaris
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.nonono infoXML can be used for describing objects metadatayes
Secondary indexesnoyes infoAll search fields are automatically indexedyesall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languageSQL-99 for query and DML statementsKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs and other access methodsHTTP APIJava API
RESTful HTTP/JSON API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Supported programming languagesJava
Python
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesyesYes, possible languages: KQL, Python, Rno
Triggersnoyes infoby using the 'percolation' featureyes, event driven architectureyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop Connectoryes infoMap-Reduce pattern can be built with XAP task executorsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationyesno
User concepts infoAccess controlAccess rights based on subaccounts and tokensRole-based access controlAzure Active Directory Authenticationno

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More resources
Alibaba Cloud Table StoreElasticsearchGigaSpacesMicrosoft Azure Data ExplorerSphinx
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