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DBMS > ArcadeDB vs. Databend vs. Splice Machine

System Properties Comparison ArcadeDB vs. Databend vs. Splice Machine

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Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonDatabend  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitearcadedb.comgithub.com/­datafuselabs/­databend
www.databend.com
splicemachine.com
Technical documentationdocs.arcadedb.comdocs.databend.comsplicemachine.com/­how-it-works
DeveloperArcade DataDatabend LabsSplice Machine
Initial release202120212014
Current releaseSeptember 20211.0.59, April 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustJava
Server operating systemsAll OS with a Java VMhosted
Linux
macOS
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesnoyes
SQL infoSupport of SQLSQL-like query language, no joinsyesyes
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
CLI Client
JDBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJavaGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoJava
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes inforelationship in graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID
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.yes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
ArcadeDBDatabendSplice Machine
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