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DBMS > GigaSpaces vs. IRONdb vs. Microsoft Azure Data Explorer vs. openGemini vs. Sphinx

System Properties Comparison GigaSpaces vs. IRONdb vs. Microsoft Azure Data Explorer vs. openGemini vs. Sphinx

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonopenGemini  Xexclude from comparisonSphinx  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully managed big data interactive analytics platformAn open source distributed Time Series DBMS with high concurrency, high performance, and high scalabilityOpen 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
Time Series DBMSRelational DBMS infocolumn orientedTime 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.09
Rank#361  Overall
#37  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.gigaspaces.comwww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-explorerwww.opengemini.org
github.com/­openGemini
sphinxsearch.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorerdocs.opengemini.org/­guidesphinxsearch.com/­docs
DeveloperGigaspaces TechnologiesCirconus LLC.MicrosoftHuawei and openGemini communitySphinx Technologies Inc.
Initial release20002017201920222001
Current release15.5, September 2020V0.10.20, January 2018cloud service with continuous releases1.1, July 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercialOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence available
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 languageJava, C++, .NetC and C++GoC++
Server operating systemsLinux
macOS
Solaris
Windows
LinuxhostedLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesInteger, Float, Boolean, Stringno
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 metadatanoyesno
Secondary indexesyesnoall fields are automatically indexedyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subsetSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP RESTProprietary protocol
Supported programming languages.Net
C++
Java
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Go
Java
JavaScript (Node.js)
Python
Rust
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesyes, in LuaYes, possible languages: KQL, Python, Rnono
Triggersyes, event driven architecturenoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud serviceShardingSharding 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
configurable replication factor, datacenter awareyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononono
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.yesnonoyes
User concepts infoAccess controlRole-based access controlnoAzure Active Directory AuthenticationAdministrators and common users accountsno

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More resources
GigaSpacesIRONdbMicrosoft Azure Data ExploreropenGeminiSphinx
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