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DBMS > eXtremeDB vs. GridDB vs. IRONdb vs. SwayDB

System Properties Comparison eXtremeDB vs. GridDB vs. IRONdb vs. SwayDB

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Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonGridDB  Xexclude from comparisonIRONdb  Xexclude from comparisonSwayDB  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringScalable in-memory time series database optimized for IoT and Big DataA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSTime Series DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitewww.mcobject.comgriddb.netwww.circonus.com/solutions/time-series-database/swaydb.simer.au
Technical documentationwww.mcobject.com/­docs/­extremedb.htmdocs.griddb.netdocs.circonus.com/irondb/category/getting-started
DeveloperMcObjectToshiba CorporationCirconus LLC.Simer Plaha
Initial release2001201320172018
Current release8.2, 20215.1, August 2022V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++C and C++Scala
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
LinuxLinux
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes infotext, numeric, histogramsno
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.no infosupport of XML interfaces availablenonono
Secondary indexesyesyesnono
SQL infoSupport of SQLyes infowith the option: eXtremeSQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP API
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresyesnoyes, in Luano
Triggersyes infoby defining eventsyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Source-replica replicationconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyes
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.yesyesnoyes
User concepts infoAccess controlAccess rights for users can be defined per databasenono
More information provided by the system vendor
eXtremeDBGridDBIRONdbSwayDB
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
GitHub trending repository
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more
Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
eXtremeDBGridDBIRONdbSwayDB
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