DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > CrateDB vs. IBM Db2 warehouse vs. Microsoft Azure Data Explorer vs. Newts vs. TimesTen

System Properties Comparison CrateDB vs. IBM Db2 warehouse vs. Microsoft Azure Data Explorer vs. Newts vs. TimesTen

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNewts  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionDistributed Database based on LuceneCloud-based data warehousing serviceFully managed big data interactive analytics platformTime Series DBMS based on CassandraIn-Memory RDBMS compatible to Oracle
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMS infocolumn orientedTime Series 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
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
Score1.37
Rank#160  Overall
#74  Relational 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
Websitecratedb.comwww.ibm.com/­products/­db2/­warehouseazure.microsoft.com/­services/­data-exploreropennms.github.io/­newtswww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationcratedb.com/­docsdocs.microsoft.com/­en-us/­azure/­data-explorergithub.com/­OpenNMS/­newts/­wikidocs.oracle.com/­database/­timesten-18.1
DeveloperCrateIBMMicrosoftOpenNMS GroupOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20132014201920141998
Current releasecloud service with continuous releases11 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
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 languageJavaJava
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedhostedLinux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesFixed schema with schema-less datatypes (dynamic)schema-freeyes
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-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.nono infoImport/export of XML data possibleyesnono
Secondary indexesyesyesall fields are automatically indexednoyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesKusto Query Language (KQL), SQL subsetnoyes
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
.NET Client API
JDBC
ODBC
OLE DB
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
Java API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
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
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaC
C++
Java
PL/SQL
Server-side scripts infoStored proceduresuser defined functions (Javascript)PL/SQL, SQL PLYes, possible languages: KQL, Python, RnoPL/SQL
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infobased on Cassandranone
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyesyes 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
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
Immediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonoyes
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 strategyACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.noyesnonoyes
User concepts infoAccess controlrights management via user accountsfine grained access rights according to SQL-standardAzure Active Directory Authenticationnofine grained access rights according to SQL-standard
More information provided by the system vendor
CrateDBIBM Db2 warehouse infoformerly named IBM dashDBMicrosoft Azure Data ExplorerNewtsTimesTen
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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
CrateDBIBM Db2 warehouse infoformerly named IBM dashDBMicrosoft Azure Data ExplorerNewtsTimesTen
Recent citations in the news

CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT
25 March 2024, PR Newswire

CrateDB Announces Availability of CrateDB on Google Cloud Marketplace
8 April 2024, Datanami

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

Crate.io Expands CrateDB Cloud with the Launch of CrateDB Edge
15 April 2021, GlobeNewswire

Real-Time Analytics Database Company CrateDB Names Lars Färnström as New CEO
1 March 2023, Business Wire

provided by Google News

Introducing the next generation of Db2 Warehouse: Our cost-effective, cloud-native data warehouse built for always-on ...
11 July 2023, IBM

Db2 Warehouse delivers 4x faster query performance than previously, while cutting storage costs by 34x
11 July 2023, IBM

The 10 Best Cloud Data Warehouse Solutions to Consider in 2024
22 October 2023, Solutions Review

Announcing the availability of Bring-Your-Own-License and Reserved Instance plans for next generation Db2 ...
7 August 2023, IBM

Data mining in Db2 Warehouse: the basics
23 June 2020, Towards Data Science

provided by Google News

Update records in a Kusto Database (public preview) | Azure updates
20 February 2024, azure.microsoft.com

Public Preview: Azure Data Explorer Add-On for Splunk | Azure updates
3 October 2023, azure.microsoft.com

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, azure.microsoft.com

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, azure.microsoft.com

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, Microsoft

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here