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DBMS > GigaSpaces vs. Machbase Neo vs. Microsoft Azure Data Explorer vs. Spark SQL vs. Sphinx

System Properties Comparison GigaSpaces vs. Machbase Neo vs. Microsoft Azure Data Explorer vs. Spark SQL vs. Sphinx

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpark SQL  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 TransactionsTimeSeries DBMS for AIoT and BigDataFully managed big data interactive analytics platformSpark SQL is a component on top of 'Spark Core' for structured data processingOpen 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 orientedRelational 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
Score0.17
Rank#337  Overall
#30  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.gigaspaces.commachbase.comazure.microsoft.com/­services/­data-explorerspark.apache.org/­sqlsphinxsearch.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlmachbase.com/­dbmsdocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperGigaspaces TechnologiesMachbaseMicrosoftApache Software FoundationSphinx Technologies Inc.
Initial release20002013201920142001
Current release15.5, September 2020V8.0, August 2023cloud service with continuous releases3.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercial infofree test version availablecommercialOpen Source infoApache 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

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Implementation languageJava, C++, .NetCScalaC++
Server operating systemsLinux
macOS
Solaris
Windows
Linux
macOS
Windows
hostedLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyesyes 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.no infoXML can be used for describing objects metadatanoyesno
Secondary indexesyesyesall fields are automatically indexednoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
Supported programming languages.Net
C++
Java
Python
Scala
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesnoYes, 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 nodesShardingShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark CoreSharding 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
selectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.nonenone
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-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 dataACIDnononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesnoyesyesyes 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.yesyes infovolatile and lookup tablenono
User concepts infoAccess controlRole-based access controlsimple password-based access controlAzure Active Directory Authenticationnono

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More resources
GigaSpacesMachbase Neo infoFormer name was InfinifluxMicrosoft Azure Data ExplorerSpark SQLSphinx
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