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DBMS > Databend vs. Microsoft Azure Table Storage vs. RavenDB vs. Spark SQL vs. Transbase

System Properties Comparison Databend vs. Microsoft Azure Table Storage vs. RavenDB vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  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 Wide Column Store for rapid development using massive semi-structured datasetsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSWide column storeDocument storeRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score2.84
Rank#101  Overall
#18  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
azure.microsoft.com/­en-us/­services/­storage/­tablesravendb.netspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.databend.comravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperDatabend LabsMicrosoftHibernating RhinosApache Software FoundationTransaction Software GmbH
Initial release20212012201020141987
Current release1.0.59, April 20235.4, July 20223.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC#ScalaC and C++
Server operating systemshosted
Linux
macOS
hostedLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.nononono
Secondary indexesnonoyesnoyes
SQL infoSupport of SQLyesnoSQL-like query language (RQL)SQL-like DML and DDL statementsyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
RESTful HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnonoyesnoyes
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesoptimistic lockingACID, Cluster-wide transaction availablenoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights based on private key authentication or shared access signaturesAuthorization levels configured per client per databasenofine grained access rights according to SQL-standard

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More resources
DatabendMicrosoft Azure Table StorageRavenDBSpark SQLTransbase
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