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DBMS > Apache Druid vs. HugeGraph vs. Microsoft Azure Table Storage vs. Warp 10

System Properties Comparison Apache Druid vs. HugeGraph vs. Microsoft Azure Table Storage vs. Warp 10

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA fast-speed and highly-scalable Graph DBMSA Wide Column Store for rapid development using massive semi-structured datasetsTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMS
Time Series DBMS
Graph DBMSWide column storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitedruid.apache.orggithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­storage/­tableswww.warp10.io
Technical documentationdruid.apache.org/­docs/­latest/­designhugegraph.apache.org/­docswww.warp10.io/­content/­02_Getting_started
DeveloperApache Software Foundation and contributorsBaiduMicrosoftSenX
Initial release2012201820122015
Current release29.0.1, April 20240.9
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0commercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsLinux
OS X
Unix
Linux
macOS
Unix
hostedLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesyesyes infoalso supports composite index and range indexnono
SQL infoSupport of SQLSQL for queryingnonono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIHTTP API
Jupyter
WebSocket
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Groovy
Java
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoasynchronous Gremlin script jobsnoyes infoWarpScript
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud serviceSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemUsers, roles and permissionsAccess rights based on private key authentication or shared access signaturesMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache DruidHugeGraphMicrosoft Azure Table StorageWarp 10
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