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

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

Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonCitus  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionIn-memory caching systemScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLFully managed big data interactive analytics platformMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeIn-Memory RDBMS compatible to Oracle
Primary database modelKey-value storeRelational DBMSRelational DBMS infocolumn orientedRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument 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
Document store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#60  Key-value stores
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score5.60
Rank#62  Overall
#35  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitecachelot.iowww.citusdata.comazure.microsoft.com/­services/­data-explorerwww.singlestore.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.citusdata.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.singlestore.comdocs.oracle.com/­database/­timesten-18.1
DeveloperMicrosoftSingleStore Inc.Oracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20152010201920131998
Current release8.1, December 2018cloud service with continuous releases8.5, January 202411 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicenseOpen Source infoAGPL, commercial license also availablecommercialcommercial infofree developer edition availablecommercial
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.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageC++CC++, Go
Server operating systemsFreeBSD
Linux
OS X
LinuxhostedLinux info64 bit version requiredAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or datenoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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 functionalityyesnono
Secondary indexesnoyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsKusto Query Language (KQL), SQL subsetyes infobut no triggers and foreign keysyes
APIs and other access methodsMemcached protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
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
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Bash
C
C#
Java
JavaScript (Node.js)
Python
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.Yes, possible languages: KQL, Python, RyesPL/SQL
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceSharding infohash partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infoother methods possible by using 3rd party extensionsyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infostores two copies of each physical data partition on two separate nodesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan define user-defined aggregate functions for map-reduce-style calculationsno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentnoyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes 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.nononoyesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAzure Active Directory AuthenticationFine grained access control via users, groups and rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
Cachelot.ioCitusMicrosoft Azure Data ExplorerSingleStore infoformer name was MemSQLTimesTen
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» 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.ioCitusMicrosoft Azure Data ExplorerSingleStore infoformer name was MemSQLTimesTen
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