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DBMS > Databend vs. Fauna vs. Microsoft Azure Table Storage vs. Splice Machine

System Properties Comparison Databend vs. Fauna vs. Microsoft Azure Table Storage vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonMicrosoft Azure Table Storage  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 complexityFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.A Wide Column Store for rapid development using massive semi-structured datasetsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Wide column storeRelational 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#143  Overall
#26  Document stores
#13  Graph DBMS
#66  Relational DBMS
#13  Time Series DBMS
Score3.55
Rank#80  Overall
#6  Wide column stores
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
fauna.comazure.microsoft.com/­en-us/­services/­storage/­tablessplicemachine.com
Technical documentationdocs.databend.comdocs.fauna.comsplicemachine.com/­how-it-works
DeveloperDatabend LabsFauna, Inc.MicrosoftSplice Machine
Initial release2021201420122014
Current release1.0.59, April 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustScalaJava
Server operating systemshosted
Linux
macOS
hostedhostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesyes
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
Secondary indexesnoyesnoyes
SQL infoSupport of SQLyesnonoyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
RESTful HTTP APIRESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoconsistent hashingSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.nonoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesIdentity management, authentication, and access controlAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standard

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DatabendFauna infopreviously named FaunaDBMicrosoft Azure Table StorageSplice Machine
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