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DBMS > Databricks vs. Ehcache vs. MarkLogic vs. Sphinx vs. Teradata Aster

System Properties Comparison Databricks vs. Ehcache vs. MarkLogic vs. Sphinx vs. Teradata Aster

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonMarkLogic  Xexclude from comparisonSphinx  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.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A widely adopted Java cache with tiered storage optionsOperational and transactional Enterprise NoSQL databaseOpen source search engine for searching in data from different sources, e.g. relational databasesPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Relational DBMS
Key-value storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.89
Rank#67  Overall
#8  Key-value stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comwww.ehcache.orgwww.marklogic.comsphinxsearch.com
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationdocs.marklogic.comsphinxsearch.com/­docs
DeveloperDatabricksTerracotta Inc, owned by Software AGMarkLogic Corp.Sphinx Technologies Inc.Teradata
Initial release20132009200120012005
Current release3.10.0, March 202211.0, December 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-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 Store
Typing infopredefined data types such as float or dateyesyesnoyes
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.yesnoyesyes infoin Aster File Store
Secondary indexesyesnoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLwith Databricks SQLnoyes infoSQL92SQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCacheJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Proprietary protocolADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesPython
R
Scala
JavaC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infovia XQuery or JavaScriptnoR packages
Triggersyes infoCache Event Listenersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta Serveryesnoneyes 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 ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceACID infocan act as a resource manager in an XA/JTA transactionnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, with Range Indexesno
User concepts infoAccess controlnoRole-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksEhcacheMarkLogicSphinxTeradata Aster
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEhcacheMarkLogicSphinxTeradata Aster
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