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DBMS > Apache Impala vs. Manticore Search vs. MarkLogic vs. Spark SQL

System Properties Comparison Apache Impala vs. Manticore Search vs. MarkLogic vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonManticore Search  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopMulti-storage database for search, including full-text search.Operational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSSearch engineDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
Secondary database modelsDocument storeTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.29
Rank#302  Overall
#21  Search engines
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
Websiteimpala.apache.orgmanticoresearch.comwww.marklogic.comspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlmanual.manticoresearch.comdocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaManticore SoftwareMarkLogic Corp.Apache Software Foundation
Initial release2013201720012014
Current release4.1.0, June 20226.0, February 202311.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPL version 2commercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++Scala
Server operating systemsLinuxFreeBSD
Linux
macOS
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesFixed schemaschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyesyes
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.noCan index from XMLyesno
Secondary indexesyesyes infofull-text index on all search fieldsyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageyes infoSQL92SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
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
Supported programming languagesAll languages supporting JDBC/ODBCElixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsyes infovia XQuery or JavaScriptno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSynchronous replication based on Galera libraryyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infoisolated transactions for atomic changes and binary logging for safe writesACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, with Range Indexesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoRole-based access control at the document and subdocument levelsno

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More resources
Apache ImpalaManticore SearchMarkLogicSpark SQL
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