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DBMS > Citus vs. CrateDB vs. IBM Cloudant vs. Microsoft Azure Data Explorer vs. SwayDB

System Properties Comparison Citus vs. CrateDB vs. IBM Cloudant vs. Microsoft Azure Data Explorer vs. SwayDB

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonCrateDB  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLDistributed Database based on LuceneDatabase as a Service offering based on Apache CouchDBFully managed big data interactive analytics platformAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document storeRelational DBMS infocolumn orientedKey-value store
Secondary database modelsDocument storeRelational DBMSDocument 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
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score2.68
Rank#106  Overall
#20  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitewww.citusdata.comcratedb.comwww.ibm.com/­products/­cloudantazure.microsoft.com/­services/­data-explorerswaydb.simer.au
Technical documentationdocs.citusdata.comcratedb.com/­docscloud.ibm.com/­docs/­Cloudantdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperCrateIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014MicrosoftSimer Plaha
Initial release20102013201020192018
Current release8.1, December 2018cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen SourcecommercialcommercialOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageCJavaErlangScala
Server operating systemsLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedhosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.yes infospecific XML type available, but no XML query functionalitynonoyesno
Secondary indexesyesyesyesall fields are automatically indexedno
SQL infoSupport of SQLyes infostandard, with numerous extensionsyes, but no triggers and constraints, and PostgreSQL compatibilitynoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
RESTful HTTP/JSON APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C#
Java
JavaScript
Objective-C
PHP
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Kotlin
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions (Javascript)View functions (Map-Reduce) in JavaScriptYes, possible languages: KQL, Python, Rno
Triggersyesnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsConfigurable replication on table/partition-levelMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyno infoatomic operations within a document possiblenoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic lockingyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardrights management via user accountsAccess rights for users can be defined per databaseAzure Active Directory Authenticationno
More information provided by the system vendor
CitusCrateDBIBM CloudantMicrosoft Azure Data ExplorerSwayDB
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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CitusCrateDBIBM CloudantMicrosoft Azure Data ExplorerSwayDB
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