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DBMS > GigaSpaces vs. Manticore Search vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. Sadas Engine

System Properties Comparison GigaSpaces vs. Manticore Search vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. Sadas Engine

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsMulti-storage database for search, including full-text search.Fully managed big data interactive analytics platformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Search engineRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
Time Series DBMS infousing the Manticore Columnar LibraryDocument 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
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.22
Rank#312  Overall
#21  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.95
Rank#100  Overall
#17  Document stores
#17  Key-value stores
#50  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitewww.gigaspaces.commanticoresearch.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­nosql/­technologies/­nosqlwww.sadasengine.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperGigaspaces TechnologiesManticore SoftwareMicrosoftOracleSADAS s.r.l.
Initial release20002017201920112006
Current release15.5, September 20206.0, February 2023cloud service with continuous releases23.3, December 20238.0
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoGPL version 2commercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)commercial infofree trial version 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++JavaC++
Server operating systemsLinux
macOS
Solaris
Windows
FreeBSD
Linux
macOS
Windows
hostedLinux
Solaris SPARC/x86
AIX
Linux
Windows
Data schemeschema-freeFixed schemaFixed schema with schema-less datatypes (dynamic)Support Fixed schema and Schema-less deployment with the ability to interoperate between them.yes
Typing infopredefined data types such as float or dateyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesoptionalyes
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 metadataCan index from XMLyesnono
Secondary indexesyesyes infofull-text index on all search fieldsall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsyes
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
Supported programming languages.Net
C++
Java
Python
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyesuser defined functionsYes, 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 nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Synchronous replication based on Galera libraryyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Electable source-replica replication per shard. Support distributed global deployment with Multi-region table featurenone
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-sparkwith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency infodepending on configuration
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infoisolated transactions for atomic changes and binary logging for safe writesnoconfigurable infoACID within a storage node (=shard)
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infooff heap cacheyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlRole-based access controlnoAzure Active Directory AuthenticationAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
GigaSpacesManticore SearchMicrosoft Azure Data ExplorerOracle NoSQLSadas Engine
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