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DBMS > Apache IoTDB vs. Drizzle vs. GigaSpaces vs. GridGain vs. PouchDB

System Properties Comparison Apache IoTDB vs. Drizzle vs. GigaSpaces vs. GridGain vs. PouchDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDrizzle  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGridGain  Xexclude from comparisonPouchDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsGridGain is an in-memory computing platform, built on Apache IgniteJavaScript DBMS with an API inspired by CouchDB
Primary database modelTime Series DBMSRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Columnar
Key-value store
Object oriented DBMS
Relational DBMS
Document store
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.91
Rank#197  Overall
#33  Document stores
#7  Object oriented DBMS
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score2.18
Rank#114  Overall
#21  Document stores
Websiteiotdb.apache.orgwww.gigaspaces.comwww.gridgain.compouchdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.gigaspaces.com/­latest/­landing.htmlwww.gridgain.com/­docs/­index.htmlpouchdb.com/­guides
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerGigaspaces TechnologiesGridGain Systems, Inc.Apache Software Foundation
Initial release20182008200020072012
Current release1.1.0, April 20237.2.4, September 201215.5, September 2020GridGain 8.5.17.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLOpen Source infoApache Version 2; Commercial licenses availablecommercial, open sourceOpen Source
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java, C++, .NetJava, C++, .Net, Python, REST, SQLJavaScript
Server operating systemsAll OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
Linux
macOS
Solaris
Windows
Linux
OS X
Solaris
Windows
z/OS
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nono infoXML can be used for describing objects metadatayesno
Secondary indexesyesyesyesyesyes infovia views
SQL infoSupport of SQLSQL-like query languageyes infowith proprietary extensionsSQL-99 for query and DML statementsANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
Native API
JDBCGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
Java
PHP
.Net
C++
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
JavaScript
Server-side scripts infoStored proceduresyesnoyesyes (compute grid and cache interceptors can be used instead)View functions in JavaScript
Triggersyesno infohooks for callbacks inside the server can be used.yes, event driven architectureyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes (replicated cache)Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infoMap-Reduce pattern can be built with XAP task executorsyes (compute grid and hadoop accelerator)yes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlyesPluggable authentication mechanisms infoe.g. LDAP, HTTPRole-based access controlRole-based access control
Security Hooks for custom implementations
no

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More resources
Apache IoTDBDrizzleGigaSpacesGridGainPouchDB
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