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DBMS > LevelDB vs. MarkLogic vs. Spark SQL vs. Teradata Aster vs. YDB

System Properties Comparison LevelDB vs. MarkLogic vs. Spark SQL vs. Teradata Aster vs. YDB

Editorial information provided by DB-Engines
NameLevelDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparisonYDB  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 processingPlatform for big data analytics on multistructured data sources and typesA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelKey-value storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMSDocument store
Relational 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
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitegithub.com/­google/­leveldbwww.marklogic.comspark.apache.org/­sqlgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
DeveloperGoogleMarkLogic Corp.Apache Software FoundationTeradataYandex
Initial release20112001201420052019
Current release1.23, February 202111.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSDcommercial inforestricted free version is availableOpen Source infoApache 2.0commercialOpen Source infoApache 2.0; commercial license available
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++Scala
Server operating systemsIllumos
Linux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
LinuxLinux
Data schemeschema-freeschema-free infoSchema can be enforcedyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File StoreFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or datenoyesyesyesyes
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 Storeno
Secondary indexesnoyesnoyesyes
SQL infoSupport of SQLnoyes infoSQL92SQL-like DML and DDL statementsyesSQL-like query language (YQL)
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
ADO.NET
JDBC
ODBC
OLE DB
RESTful HTTP API (DynamoDB compatible)
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
C#
C++
Java
Python
R
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptnoR packagesno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark CoreShardingSharding
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.Active-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
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 Indexesnonono
User concepts infoAccess controlnoRole-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standardAccess rights defined for Yandex Cloud users

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More resources
LevelDBMarkLogicSpark SQLTeradata AsterYDB
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