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

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

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonFileMaker  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrigoDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionDistributed Database based on LuceneFileMaker is a cross-platform RDBMS that includes a GUI frontend.An open source BigTable implementation based on distributed file systems such as HadoopFully managed big data interactive analytics platformA fully ACID in-memory object graph database
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSWide column storeRelational DBMS infocolumn orientedDocument store
Object oriented 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
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
Websitecratedb.comwww.claris.com/­filemakerazure.microsoft.com/­services/­data-explorerorigodb.com
Technical documentationcratedb.com/­docswww.claris.com/­resources/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerorigodb.com/­docs
DeveloperCrateClaris infoa subsidiary of AppleHypertable Inc.MicrosoftRobert Friberg et al
Initial release20131983200920192009 infounder the name LiveDB
Current release19.4.1, November 20210.9.8.11, March 2016cloud service with continuous releases
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source
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.
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++C#
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportiOS infoclient part only
Linux
OS X
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
hostedLinux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeFixed schema with schema-less datatypes (dynamic)yes
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-typesUser defined using .NET types and collections
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 indexesyesyesrestricted infoonly exact value or prefix value scansall fields are automatically indexedyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyes infovia pluginsnoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Filemaker WebDirect
JDBC
ODBC
C++ API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP API
LINQ
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
PHPC++
Java
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Server-side scripts infoStored proceduresuser defined functions (Javascript)yesnoYes, possible languages: KQL, Python, Ryes
Triggersnoyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replication, warm standby infosince Version 14selectable replication factor on file system levelyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
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 systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonodepending on model
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 strategynononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlrights management via user accountssimple rights management via user accounts and connection to external directory servicesnoAzure Active Directory AuthenticationRole based authorization
More information provided by the system vendor
CrateDBFileMakerHypertableMicrosoft Azure Data ExplorerOrigoDB
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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More resources
CrateDBFileMakerHypertableMicrosoft Azure Data ExplorerOrigoDB
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