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DBMS > Databend vs. OrigoDB vs. Splice Machine

System Properties Comparison Databend vs. OrigoDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonOrigoDB  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 complexityA fully ACID in-memory object graph databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument store
Object oriented DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.28
Rank#287  Overall
#131  Relational DBMS
Score0.00
Rank#385  Overall
#54  Document stores
#21  Object oriented DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
origodb.comsplicemachine.com
Technical documentationdocs.databend.comorigodb.com/­docssplicemachine.com/­how-it-works
DeveloperDatabend LabsRobert Friberg et alSplice Machine
Initial release20212009 infounder the name LiveDB2014
Current release1.0.59, April 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen 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
Linux
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsyes
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 infocan be achieved using .NET
Secondary indexesnoyesyes
SQL infoSupport of SQLyesnoyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
.NET Client API
HTTP API
LINQ
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.NetC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyes infoJava
Triggersnoyes infoDomain Eventsyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoclient side managed; servers are not synchronizedShared 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 methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynodepending on modelyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infoWrite ahead logyes
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 rolesRole based authorizationAccess rights for users, groups and roles according to SQL-standard

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More resources
DatabendOrigoDBSplice Machine
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