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DBMS > Apache Phoenix vs. MarkLogic vs. ReductStore vs. Spark SQL vs. Teradata Aster

System Properties Comparison Apache Phoenix vs. MarkLogic vs. ReductStore vs. Spark SQL vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonMarkLogic  Xexclude from comparisonReductStore  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.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseOperational and transactional Enterprise NoSQL databaseDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Spark 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 DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Time Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.progress.com/­marklogicgithub.com/­reductstore
www.reduct.store
spark.apache.org/­sql
Technical documentationphoenix.apache.orgwww.progress.com/­marklogic/­documentationwww.reduct.store/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationMarkLogic Corp.ReductStore LLCApache Software FoundationTeradata
Initial release20142001202320142005
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201911.0, December 20221.9, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial inforestricted free version is availableOpen Source infoBusiness Source License 1.1Open 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 languageJavaC++C++, RustScala
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
Docker
Linux
macOS
Windows
Linux
OS X
Windows
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-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 dateyesyesyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLyesyes infoSQL92SQL-like DML and DDL statementsyes
APIs and other access methodsJDBCJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functionsyes infovia XQuery or JavaScriptnoR packages
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnoneyes 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 methodsHadoop integrationyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual 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 dataACIDACID 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 Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyRole-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standard

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More resources
Apache PhoenixMarkLogicReductStoreSpark SQLTeradata Aster
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