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DBMS > Apache Druid vs. Google Cloud Datastore vs. GridGain vs. SiteWhere

System Properties Comparison Apache Druid vs. Google Cloud Datastore vs. GridGain vs. SiteWhere

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  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 PlatformGridGain is an in-memory computing platform, built on Apache IgniteM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMS
Time Series DBMS
Document storeKey-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Score0.06
Rank#367  Overall
#36  Time Series DBMS
Websitedruid.apache.orgcloud.google.com/­datastorewww.gridgain.comgithub.com/­sitewhere/­sitewhere
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmlsitewhere1.sitewhere.io/­index.html
DeveloperApache Software Foundation and contributorsGoogleGridGain Systems, Inc.SiteWhere
Initial release2012200820072010
Current release29.0.1, April 2024GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen 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 languageJavaJava, C++, .NetJava
Server operating systemsLinux
OS X
Unix
hostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyespredefined scheme
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP REST
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnousing Google App Engineyes (compute grid and cache interceptors can be used instead)
TriggersnoCallbacks using the Google Apps Engineyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication using Paxosyes (replicated cache)selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
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.nonoyesno
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)Security Hooks for custom implementationsUsers with fine-grained authorization concept

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More resources
Apache DruidGoogle Cloud DatastoreGridGainSiteWhere
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