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DBMS > Alibaba Cloud Table Store vs. Apache Druid vs. InfluxDB vs. Microsoft Azure Data Explorer vs. Oracle NoSQL

System Properties Comparison Alibaba Cloud Table Store vs. Apache Druid vs. InfluxDB vs. Microsoft Azure Data Explorer vs. Oracle NoSQL

Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonApache Druid  Xexclude from comparisonInfluxDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle NoSQL  Xexclude from comparison
DescriptionA fully managed Wide Column Store for large quantities of semi-structured data with real-time accessOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDBMS for storing time series, events and metricsFully managed big data interactive analytics platformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes
Primary database modelWide column storeRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith GEO packageDocument 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
Score0.31
Rank#297  Overall
#11  Wide column stores
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score24.39
Rank#28  Overall
#1  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score3.05
Rank#97  Overall
#17  Document stores
#16  Key-value stores
#50  Relational DBMS
Websitewww.alibabacloud.com/­product/­table-storedruid.apache.orgwww.influxdata.com/­products/­influxdb-overviewazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­nosql/­technologies/­nosql
Technical documentationwww.alibabacloud.com/­help/­en/­tablestoredruid.apache.org/­docs/­latest/­designdocs.influxdata.com/­influxdbdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.html
DeveloperAlibabaApache Software Foundation and contributorsMicrosoftOracle
Initial release20162012201320192011
Current release29.0.1, April 20242.7.6, April 2024cloud service with continuous releases24.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoMIT-License; commercial enterprise version availablecommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoJava
Server operating systemshostedLinux
OS X
Unix
Linux
OS X infothrough Homebrew
hostedLinux
Solaris SPARC/x86
Data schemeschema-freeyes infoschema-less columns are supportedschema-freeFixed schema with schema-less datatypes (dynamic)Support Fixed schema and Schema-less deployment with the ability to interoperate between them.
Typing infopredefined data types such as float or dateyesyesNumeric data and Stringsyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesoptional
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.nononoyesno
Secondary indexesnoyesnoall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL for queryingSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statements
APIs and other access methodsHTTP APIJDBC
RESTful HTTP/JSON API
HTTP API
JSON over UDP
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesJava
Python
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononoYes, possible languages: KQL, Python, Rno
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infomanual/auto, time-basedSharding infoin enterprise version onlySharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyes, via HDFS, S3 or other storage enginesselectable replication factor infoin enterprise version onlyyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnononoconfigurable infoACID within a storage node (=shard)
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.nonoyes infoDepending on used storage enginenoyes infooff heap cache
User concepts infoAccess controlAccess rights based on subaccounts and tokensRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemsimple rights management via user accountsAzure Active Directory AuthenticationAccess rights for users and roles
More information provided by the system vendor
Alibaba Cloud Table StoreApache DruidInfluxDBMicrosoft Azure Data ExplorerOracle NoSQL
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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