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DBMS > CrateDB vs. HugeGraph vs. IBM Db2 warehouse vs. InterSystems IRIS vs. Microsoft Azure Data Explorer

System Properties Comparison CrateDB vs. HugeGraph vs. IBM Db2 warehouse vs. InterSystems IRIS vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionDistributed Database based on LuceneA fast-speed and highly-scalable Graph DBMSCloud-based data warehousing serviceA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityFully managed big data interactive analytics platform
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Graph DBMSRelational DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMS infocolumn oriented
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
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitecratedb.comgithub.com/­hugegraph
hugegraph.apache.org
www.ibm.com/­products/­db2/­warehousewww.intersystems.com/­products/­intersystems-irisazure.microsoft.com/­services/­data-explorer
Technical documentationcratedb.com/­docshugegraph.apache.org/­docsdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperCrateBaiduIBMInterSystemsMicrosoft
Initial release20132018201420182019
Current release0.92023.3, June 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
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 supportLinux
macOS
Unix
hostedAIX
Linux
macOS
Ubuntu
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesdepending on used data modelFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonono infoImport/export of XML data possibleyesyes
Secondary indexesyesyes infoalso supports composite index and range indexyesyesall fields are automatically indexed
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoyesyesKusto Query Language (KQL), SQL subset
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
.NET Client API
JDBC
ODBC
OLE DB
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
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
Groovy
Java
Python
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functions (Javascript)asynchronous Gremlin script jobsPL/SQL, SQL PLyesYes, possible languages: KQL, Python, R
Triggersnonoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyes infodepending on used storage backend, e.g. Cassandra and HBaseyesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparknonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphyesyesno
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 strategyACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesyesyesno
User concepts infoAccess controlrights management via user accountsUsers, roles and permissionsfine grained access rights according to SQL-standardyesAzure Active Directory Authentication
More information provided by the system vendor
CrateDBHugeGraphIBM Db2 warehouse infoformerly named IBM dashDBInterSystems IRISMicrosoft Azure Data Explorer
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
» 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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CrateDBHugeGraphIBM Db2 warehouse infoformerly named IBM dashDBInterSystems IRISMicrosoft Azure Data Explorer
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