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DBMS > Apache Pinot vs. Geode vs. MarkLogic vs. Spark SQL vs. Teradata Aster

System Properties Comparison Apache Pinot vs. Geode vs. MarkLogic vs. Spark SQL vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGeode  Xexclude from comparisonMarkLogic  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.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesOperational 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 types
Primary database modelRelational DBMSKey-value storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score1.86
Rank#134  Overall
#24  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
Websitepinot.apache.orggeode.apache.orgwww.progress.com/­marklogicspark.apache.org/­sql
Technical documentationdocs.pinot.apache.orggeode.apache.org/­docswww.progress.com/­marklogic/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.MarkLogic Corp.Apache Software FoundationTeradata
Initial release20152002200120142005
Current release1.0.0, September 20231.1, February 201711.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses available as Gemfirecommercial inforestricted free version is availableOpen 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 languageJavaJavaC++Scala
Server operating systemsAll OS with a Java JDK11 or higherAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux
OS X
Windows
Linux
OS X
Windows
Linux
Data schemeyesschema-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 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 indexesnoyesnoyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language (OQL)yes infoSQL92SQL-like DML and DDL statementsyes
APIs and other access methodsJDBCJava Client API
Memcached protocol
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
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
Python
.Net
All JVM based languages
C++
Groovy
Java
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functionsyes infovia XQuery or JavaScriptnoR packages
Triggersyes infoCache Event Listenersyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesnoneyes 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 jobsyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 datayes, on a single nodeACID infocan act as a resource manager in an XA/JTA transactionnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, with Range Indexesnono
User concepts infoAccess controlAccess rights per client and object definableRole-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standard

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More resources
Apache PinotGeodeMarkLogicSpark SQLTeradata Aster
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