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DBMS > AgensGraph vs. Apache Druid vs. Microsoft Azure Table Storage vs. Riak KV

System Properties Comparison AgensGraph vs. Apache Druid vs. Microsoft Azure Table Storage vs. Riak KV

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonApache Druid  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA Wide Column Store for rapid development using massive semi-structured datasetsDistributed, fault tolerant key-value store
Primary database modelGraph DBMS
Relational DBMS
Relational DBMS
Time Series DBMS
Wide column storeKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitebitnine.net/­agensgraphdruid.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationbitnine.net/­documentationdruid.apache.org/­docs/­latest/­designwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperBitnine Global Inc.Apache Software Foundation and contributorsMicrosoftOpenSource, formerly Basho Technologies
Initial release2016201220122009
Current release2.1, December 201829.0.1, April 20243.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache license v2commercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaErlang
Server operating systemsLinux
OS X
Windows
Linux
OS X
Unix
hostedLinux
OS X
Data schemedepending on used data modelyes infoschema-less columns are supportedschema-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 for queryingnono
APIs and other access methodsCypher Query Language
JDBC
JDBC
RESTful HTTP/JSON API
RESTful HTTP APIHTTP API
Native Erlang Interface
Supported programming languagesC
Java
JavaScript
Python
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
.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 proceduresyesnonoErlang
Triggersnononoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceSharding infomanual/auto, time-basedSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, via HDFS, S3 or other storage enginesyes 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 methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic 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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights based on private key authentication or shared access signaturesyes, using Riak Security

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More resources
AgensGraphApache DruidMicrosoft Azure Table StorageRiak KV
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