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DBMS > Apache Druid vs. Google Cloud Datastore vs. Riak KV vs. SiteWhere

System Properties Comparison Apache Druid vs. Google Cloud Datastore vs. Riak KV vs. SiteWhere

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRiak KV  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, fault tolerant key-value storeM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMS
Time Series DBMS
Document storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitedruid.apache.orgcloud.google.com/­datastoregithub.com/­sitewhere/­sitewhere
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­datastore/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestsitewhere1.sitewhere.io/­index.html
DeveloperApache Software Foundation and contributorsGoogleOpenSource, formerly Basho TechnologiesSiteWhere
Initial release2012200820092010
Current release29.0.1, April 20243.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaErlangJava
Server operating systemsLinux
OS X
Unix
hostedLinux
OS X
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-freeschema-freepredefined scheme
Typing infopredefined data types such as float or dateyesyes, details herenoyes
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 indexesyesyesrestrictedno
SQL infoSupport of SQLSQL for queryingSQL-like query language (GQL)nono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Native Erlang Interface
HTTP REST
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
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 proceduresnousing Google App EngineErlang
TriggersnoCallbacks using the Google Apps Engineyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infono "single point of failure"Sharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication using Paxosselectable replication factorselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
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 controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes, using Riak SecurityUsers with fine-grained authorization concept

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More resources
Apache DruidGoogle Cloud DatastoreRiak KVSiteWhere
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