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DBMS > LevelDB vs. MarkLogic vs. Spark SQL vs. SQream DB vs. Teradata Aster

System Properties Comparison LevelDB vs. MarkLogic vs. Spark SQL vs. SQream DB vs. Teradata Aster

Editorial information provided by DB-Engines
NameLevelDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  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.
DescriptionEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesOperational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloadsPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value storeDocument 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
Score2.25
Rank#115  Overall
#19  Key-value stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websitegithub.com/­google/­leveldbwww.marklogic.comspark.apache.org/­sqlsqream.com
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperGoogleMarkLogic Corp.Apache Software FoundationSQream TechnologiesTeradata
Initial release20112001201420172005
Current release1.23, February 202111.0, December 20223.5.0 ( 2.13), September 20232022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoBSDcommercial inforestricted free version is availableOpen Source infoApache 2.0commercialcommercial
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 languageC++C++ScalaC++, CUDA, Haskell, Java, Scala
Server operating systemsIllumos
Linux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
LinuxLinux
Data schemeschema-freeschema-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 datenoyesyesyes, ANSI Standard SQL Typesyes
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 indexesnoyesnonoyes
SQL infoSupport of SQLnoyes infoSQL92SQL-like DML and DDL statementsyesyes
APIs and other access methodsJava 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
.Net
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptnouser defined functions in PythonR packages
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Corehorizontal and vertical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnonenoneyes 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 jobsnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infocan act as a resource manager in an XA/JTA transactionnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith automatic compression on writesyesyesyesyes
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 controlnoRole-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standard

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More resources
LevelDBMarkLogicSpark SQLSQream DBTeradata Aster
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