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DBMS > Databend vs. MarkLogic vs. OushuDB vs. Spark SQL vs. Teradata Aster

System Properties Comparison Databend vs. MarkLogic vs. OushuDB vs. Spark SQL vs. Teradata Aster

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonMarkLogic  Xexclude from comparisonOushuDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityOperational and transactional Enterprise NoSQL databaseA data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learningSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score0.10
Rank#355  Overall
#154  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.progress.com/­marklogicwww.oushu.com/­product/­oushuDBspark.apache.org/­sql
Technical documentationdocs.databend.comwww.progress.com/­marklogic/­documentationwww.oushu.com/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabend LabsMarkLogic Corp.OushuApache Software FoundationTeradata
Initial release2021200120142005
Current release1.0.59, April 202311.0, December 20224.0.1, August 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial inforestricted free version is availablecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC++Scala
Server operating systemshosted
Linux
macOS
Linux
OS X
Windows
LinuxLinux
OS X
Windows
Linux
Data schemeyesschema-free infoSchema can be enforcedyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyesnoyes infoin Aster File Store
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLyesyes infoSQL92Full-featured ANSI SQL supportSQL-like DML and DDL statementsyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptyesnoR packages
Triggersnoyesyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyesyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsHadoop integrationyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infocan act as a resource manager in an XA/JTA transactionACIDnoACID
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.yes, with Range Indexesnono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesRole-based access control at the document and subdocument levelsKerberos, SSL and role based accessnofine grained access rights according to SQL-standard

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More resources
DatabendMarkLogicOushuDBSpark SQLTeradata Aster
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