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DBMS > Databend vs. GridDB vs. Splice Machine

System Properties Comparison Databend vs. GridDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGridDB  Xexclude from comparisonSplice Machine  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 complexityScalable in-memory time series database optimized for IoT and Big DataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
griddb.netsplicemachine.com
Technical documentationdocs.databend.comdocs.griddb.netsplicemachine.com/­how-it-works
DeveloperDatabend LabsToshiba CorporationSplice Machine
Initial release202120132014
Current release1.0.59, April 20235.1, August 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustC++Java
Server operating systemshosted
Linux
macOS
LinuxLinux
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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
Secondary indexesnoyesyes
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoJava
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users can be defined per databaseAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatabendGridDBSplice Machine
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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DatabendGridDBSplice Machine
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