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DBMS > GigaSpaces vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Riak TS vs. Sphinx

System Properties Comparison GigaSpaces vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Riak TS vs. Sphinx

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonObjectBox  Xexclude from comparisonRiak TS  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsFully managed big data interactive analytics platformExtremely fast embedded database for small devices, IoT and MobileRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMS infocolumn orientedObject oriented DBMSTime Series DBMSSearch engine
Secondary database modelsGraph 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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.gigaspaces.comazure.microsoft.com/­services/­data-explorerobjectbox.iosphinxsearch.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.objectbox.iowww.tiot.jp/­riak-docs/­riak/­ts/­latestsphinxsearch.com/­docs
DeveloperGigaspaces TechnologiesMicrosoftObjectBox LimitedOpen Source, formerly Basho TechnologiesSphinx Technologies Inc.
Initial release20002019201720152001
Current release15.5, September 2020cloud service with continuous releases3.0.0, September 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoApache License 2.0Open SourceOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC and C++ErlangC++
Server operating systemsLinux
macOS
Solaris
Windows
hostedAndroid
iOS
Linux
macOS
Windows
Linux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesnono
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.no infoXML can be used for describing objects metadatayesnono
Secondary indexesyesall fields are automatically indexedyesrestrictedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-99 for query and DML statementsKusto Query Language (KQL), SQL subsetnoyes, limitedSQL-like query language (SphinxQL)
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary native APIHTTP API
Native Erlang Interface
Proprietary protocol
Supported programming languages.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, RnoErlangno
Triggersyes, event driven architectureyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-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.online/offline synchronization between client and serverselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
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.yesnono
User concepts infoAccess controlRole-based access controlAzure Active Directory Authenticationyesnono
More information provided by the system vendor
GigaSpacesMicrosoft Azure Data ExplorerObjectBoxRiak TSSphinx
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