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DBMS > Databend vs. Datomic vs. GigaSpaces vs. GridDB

System Properties Comparison Databend vs. Datomic vs. GigaSpaces vs. GridDB

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonDatomic  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsScalable in-memory time series database optimized for IoT and Big Data
Primary database modelRelational DBMSRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMS
Secondary database modelsGraph DBMS
Search engine
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.28
Rank#287  Overall
#131  Relational DBMS
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score0.91
Rank#197  Overall
#33  Document stores
#7  Object oriented DBMS
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.datomic.comwww.gigaspaces.comgriddb.net
Technical documentationdocs.databend.comdocs.datomic.comdocs.gigaspaces.com/­latest/­landing.htmldocs.griddb.net
DeveloperDatabend LabsCognitectGigaspaces TechnologiesToshiba Corporation
Initial release2021201220002013
Current release1.0.59, April 20231.0.7180, July 202415.5, September 20205.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freeOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustJava, ClojureJava, C++, .NetC++
Server operating systemshosted
Linux
macOS
All OS with a Java VMLinux
macOS
Solaris
Windows
Linux
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infonumerical, string, blob, geometry, boolean, timestamp
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.nonono infoXML can be used for describing objects metadatano
Secondary indexesnoyesyesyes
SQL infoSupport of SQLyesnoSQL-99 for query and DML statementsSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
RESTful HTTP APIGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Clojure
Java
.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyesno
TriggersnoBy using transaction functionsyes, event driven architectureyes
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoMap-Reduce pattern can be built with XAP task executorsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesnoRole-based access controlAccess rights for users can be defined per database

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More resources
DatabendDatomicGigaSpacesGridDB
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