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DBMS > GigaSpaces vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. NSDb vs. PouchDB

System Properties Comparison GigaSpaces vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. NSDb vs. PouchDB

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNSDb  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsCommon in IBM host environments, 2 different versions for host and Windows/LinuxFully managed big data interactive analytics platformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesJavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS infocolumn orientedTime Series DBMSDocument store
Secondary database modelsGraph DBMS
Search engine
Document store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
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
Score125.90
Rank#9  Overall
#6  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitewww.gigaspaces.comwww.ibm.com/­products/­db2azure.microsoft.com/­services/­data-explorernsdb.iopouchdb.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlwww.ibm.com/­docs/­en/­db2docs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architecturepouchdb.com/­guides
DeveloperGigaspaces TechnologiesIBMMicrosoftApache Software Foundation
Initial release20001983 infohost version201920172012
Current release15.5, September 202012.1, October 2016cloud service with continuous releases7.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercial infofree version is availablecommercialOpen Source infoApache Version 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC and C++Java, ScalaJavaScript
Server operating systemsLinux
macOS
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
z/OS
hostedLinux
macOS
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
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-typesyes: int, bigint, decimal, 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 metadatayesnono
Secondary indexesyesyesall fields are automatically indexedall fields are automatically indexedyes infovia views
SQL infoSupport of SQLSQL-99 for query and DML statementsyesKusto Query Language (KQL), SQL subsetSQL-like query languageno
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languages.Net
C++
Java
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Scala
JavaScript
Server-side scripts infoStored proceduresyesyesYes, possible languages: KQL, Python, RnoView functions in JavaScript
Triggersyes, event driven architectureyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoonly with Windows/Unix/Linux VersionSharding infoImplicit feature of the cloud serviceShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infowith separate tools (MQ, InfoSphere)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
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-sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationno

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More resources
GigaSpacesIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerNSDbPouchDB
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