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DBMS > Cachelot.io vs. Citus vs. GridDB vs. Microsoft Azure Data Explorer vs. TimesTen

System Properties Comparison Cachelot.io vs. Citus vs. GridDB vs. Microsoft Azure Data Explorer vs. TimesTen

Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonCitus  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionIn-memory caching systemScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLScalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformIn-Memory RDBMS compatible to Oracle
Primary database modelKey-value storeRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
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
Score0.00
Rank#396  Overall
#64  Key-value stores
Score2.15
Rank#123  Overall
#60  Relational DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score1.35
Rank#165  Overall
#75  Relational DBMS
Websitecachelot.iowww.citusdata.comgriddb.netazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.citusdata.comdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­database/­timesten-18.1
DeveloperToshiba CorporationMicrosoftOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20152010201320191998
Current release8.1, December 20185.1, August 2022cloud service with continuous releases11 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicenseOpen Source infoAGPL, commercial license also availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CC++
Server operating systemsFreeBSD
Linux
OS X
LinuxLinuxhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or datenoyesyes infonumerical, string, blob, geometry, boolean, timestampyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.noyes infospecific XML type available, but no XML query functionalitynoyesno
Secondary indexesnoyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetyes
APIs and other access methodsMemcached protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noYes, possible languages: KQL, Python, RPL/SQL
Triggersnoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentnoyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesnoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users can be defined per databaseAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
Cachelot.ioCitusGridDBMicrosoft Azure Data ExplorerTimesTen
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Cachelot.ioCitusGridDBMicrosoft Azure Data ExplorerTimesTen
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