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DBMS > Apache Phoenix vs. DolphinDB vs. Microsoft Azure Table Storage vs. Riak TS

System Properties Comparison Apache Phoenix vs. DolphinDB vs. Microsoft Azure Table Storage vs. Riak TS

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDolphinDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRiak TS  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A Wide Column Store for rapid development using massive semi-structured datasetsRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelRelational DBMSTime Series DBMSWide column storeTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Websitephoenix.apache.orgwww.dolphindb.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationphoenix.apache.orgdocs.dolphindb.cn/­en/­help200/­index.htmlwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperApache Software FoundationDolphinDB, IncMicrosoftOpen Source, formerly Basho Technologies
Initial release2014201820122015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019v2.00.4, January 20223.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community version availablecommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Erlang
Server operating systemsLinux
Unix
Windows
Linux
Windows
hostedLinux
OS X
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesnorestricted
SQL infoSupport of SQLyesSQL-like query languagenoyes, limited
APIs and other access methodsJDBCJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
RESTful HTTP APIHTTP API
Native Erlang Interface
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsyesnoErlang
Triggersnononoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesoptimistic 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.yesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAdministrators, Users, GroupsAccess rights based on private key authentication or shared access signaturesno

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More resources
Apache PhoenixDolphinDBMicrosoft Azure Table StorageRiak TS
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