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DBMS > Apache Pinot vs. Ehcache vs. Heroic vs. MarkLogic vs. Teradata Aster

System Properties Comparison Apache Pinot vs. Ehcache vs. Heroic vs. MarkLogic vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonEhcache  Xexclude from comparisonHeroic  Xexclude from comparisonMarkLogic  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.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyA widely adopted Java cache with tiered storage optionsTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchOperational and transactional Enterprise NoSQL databasePlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSKey-value storeTime Series DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score4.89
Rank#67  Overall
#8  Key-value stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Websitepinot.apache.orgwww.ehcache.orggithub.com/­spotify/­heroicwww.marklogic.com
Technical documentationdocs.pinot.apache.orgwww.ehcache.org/­documentationspotify.github.io/­heroicdocs.marklogic.com
DeveloperApache Software Foundation and contributorsTerracotta Inc, owned by Software AGSpotifyMarkLogic Corp.Teradata
Initial release20152009201420012005
Current release1.0.0, September 20233.10.0, March 202211.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercial inforestricted free version is availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaC++
Server operating systemsAll OS with a Java JDK11 or higherAll OS with a Java VMLinux
OS X
Windows
Linux
Data schemeyesschema-freeschema-freeschema-free infoSchema can be enforcedFlexible 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.nonoyesyes infoin Aster File Store
Secondary indexesnoyes infovia Elasticsearchyesyes
SQL infoSupport of SQLSQL-like query languagenonoyes infoSQL92yes
APIs and other access methodsJDBCJCacheHQL (Heroic Query Language, a JSON-based language)
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
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
Python
JavaC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonoyes infovia XQuery or JavaScriptR packages
Triggersyes infoCache Event Listenersnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoby using Terracotta ServerShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serveryesyesyes 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 methodsnonoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
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 datayes infosupports JTA and can work as an XA resourcenoACID infocan act as a resource manager in an XA/JTA transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, with Range Indexesno
User concepts infoAccess controlnoRole-based access control at the document and subdocument levelsfine grained access rights according to SQL-standard

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More resources
Apache PinotEhcacheHeroicMarkLogicTeradata Aster
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