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DBMS > CrateDB vs. FileMaker vs. Microsoft Azure Data Explorer vs. OrigoDB vs. Vitess

System Properties Comparison CrateDB vs. FileMaker vs. Microsoft Azure Data Explorer vs. OrigoDB vs. Vitess

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonFileMaker  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrigoDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionDistributed Database based on LuceneFileMaker is a cross-platform RDBMS that includes a GUI frontend.Fully managed big data interactive analytics platformA fully ACID in-memory object graph databaseScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMS infocolumn orientedDocument store
Object oriented DBMS
Relational DBMS
Secondary database modelsRelational 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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score48.20
Rank#20  Overall
#14  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitecratedb.comwww.claris.com/­filemakerazure.microsoft.com/­services/­data-explorerorigodb.comvitess.io
Technical documentationcratedb.com/­docswww.claris.com/­resources/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerorigodb.com/­docsvitess.io/­docs
DeveloperCrateClaris infoa subsidiary of AppleMicrosoftRobert Friberg et alThe Linux Foundation, PlanetScale
Initial release2013198320192009 infounder the name LiveDB2013
Current release19.4.1, November 2021cloud service with continuous releases15.0.2, December 2022
License infoCommercial or Open SourceOpen SourcecommercialcommercialOpen SourceOpen Source infoApache Version 2.0, commercial licenses 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.
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 languageJavaC#Go
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportiOS infoclient part only
Linux
OS X
Windows
hostedLinux
Windows
Docker
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesFixed schema with schema-less datatypes (dynamic)yesyes
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-typesUser defined using .NET types and collectionsyes
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 infoA http query request can return the data in XML formatyesno infocan be achieved using .NET
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyes infovia pluginsKusto Query Language (KQL), SQL subsetnoyes infowith proprietary extensions
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Filemaker WebDirect
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP API
LINQ
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.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
PHP.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.NetAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions (Javascript)yesYes, possible languages: KQL, Python, Ryesyes infoproprietary syntax
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoDomain Eventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replication, warm standby infosince Version 14yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnodepending on modelyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategynonoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlrights management via user accountssimple rights management via user accounts and connection to external directory servicesAzure Active Directory AuthenticationRole based authorizationUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
CrateDBFileMakerMicrosoft Azure Data ExplorerOrigoDBVitess
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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CrateDBFileMakerMicrosoft Azure Data ExplorerOrigoDBVitess
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