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DBMS > CrateDB vs. Microsoft Azure Data Explorer vs. Newts vs. TimesTen vs. Vitess

System Properties Comparison CrateDB vs. Microsoft Azure Data Explorer vs. Newts vs. TimesTen vs. Vitess

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNewts  Xexclude from comparisonTimesTen  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionDistributed Database based on LuceneFully managed big data interactive analytics platformTime Series DBMS based on CassandraIn-Memory RDBMS compatible to OracleScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMS infocolumn orientedTime Series DBMSRelational DBMSRelational 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
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.07
Rank#375  Overall
#41  Time Series DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitecratedb.comazure.microsoft.com/­services/­data-exploreropennms.github.io/­newtswww.oracle.com/­database/­technologies/­related/­timesten.htmlvitess.io
Technical documentationcratedb.com/­docsdocs.microsoft.com/­en-us/­azure/­data-explorergithub.com/­OpenNMS/­newts/­wikidocs.oracle.com/­database/­timesten-18.1vitess.io/­docs
DeveloperCrateMicrosoftOpenNMS GroupOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005The Linux Foundation, PlanetScale
Initial release20132019201419982013
Current releasecloud service with continuous releases11 Release 2 (11.2.2.8.0)15.0.2, December 2022
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
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 languageJavaJavaGo
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedLinux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Docker
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)Fixed schema with schema-less datatypes (dynamic)schema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyes
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.noyesnono
Secondary indexesyesall fields are automatically indexednoyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityKusto Query Language (KQL), SQL subsetnoyesyes infowith proprietary extensions
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
Java API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
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
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaC
C++
Java
PL/SQL
Ada
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)Yes, possible languages: KQL, Python, RnoPL/SQLyes infoproprietary syntax
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infobased on CassandranoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Immediate Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyesyes 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 infoby means of logfiles and checkpointsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesyes
User concepts infoAccess controlrights management via user accountsAzure Active Directory Authenticationnofine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
CrateDBMicrosoft Azure Data ExplorerNewtsTimesTenVitess
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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CrateDBMicrosoft Azure Data ExplorerNewtsTimesTenVitess
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