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DBMS > CrateDB vs. HugeGraph vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Yanza

System Properties Comparison CrateDB vs. HugeGraph vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Yanza

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonObjectBox  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDistributed Database based on LuceneA fast-speed and highly-scalable Graph DBMSFully managed big data interactive analytics platformExtremely fast embedded database for small devices, IoT and MobileTime Series DBMS for IoT Applications
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Graph DBMSRelational DBMS infocolumn orientedObject oriented DBMSTime Series 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
Time Series 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
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Websitecratedb.comgithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­services/­data-explorerobjectbox.ioyanza.com
Technical documentationcratedb.com/­docshugegraph.apache.org/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.objectbox.io
DeveloperCrateBaiduMicrosoftObjectBox LimitedYanza
Initial release20132018201920172015
Current release0.9cloud service with continuous releases
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache License 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono infobut mainly used as a service provided by Yanza
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 languageJavaJavaC and C++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
macOS
Unix
hostedAndroid
iOS
Linux
macOS
Windows
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesFixed schema with schema-less datatypes (dynamic)yesschema-free
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-typesyesno
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.nonoyesnono
Secondary indexesyesyes infoalso supports composite index and range indexall fields are automatically indexedyesno
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoKusto Query Language (KQL), SQL subsetnono
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
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary native APIHTTP 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
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functions (Javascript)asynchronous Gremlin script jobsYes, possible languages: KQL, Python, Rnono
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud servicenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.online/offline synchronization between client and servernone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparkSpark 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 ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphnoyesno
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 strategyACIDnoACIDno
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.noyesnono
User concepts infoAccess controlrights management via user accountsUsers, roles and permissionsAzure Active Directory Authenticationyesno
More information provided by the system vendor
CrateDBHugeGraphMicrosoft Azure Data ExplorerObjectBoxYanza
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
CrateDBHugeGraphMicrosoft Azure Data ExplorerObjectBoxYanza
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