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DBMS > Apache Impala vs. Datomic vs. MarkLogic vs. Riak KV

System Properties Comparison Apache Impala vs. Datomic vs. MarkLogic vs. Riak KV

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonMarkLogic  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityOperational and transactional Enterprise NoSQL databaseDistributed, fault tolerant key-value store
Primary database modelRelational DBMSRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Key-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score4.15
Rank#70  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#8  Search engines
Score3.84
Rank#76  Overall
#9  Key-value stores
Websiteimpala.apache.orgwww.datomic.comwww.progress.com/­marklogic
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comwww.progress.com/­marklogic/­documentationwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectMarkLogic Corp.OpenSource, formerly Basho Technologies
Initial release2013201220012009
Current release4.1.0, June 20221.0.7180, July 202411.0, December 20223.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercial inforestricted free version is availableOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureC++Erlang
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Windows
Linux
OS X
Data schemeyesyesschema-free infoSchema can be enforcedschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nonoyesno
Secondary indexesyesyesyesrestricted
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoSQL92no
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIJava 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 API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsyes infovia XQuery or JavaScriptErlang
TriggersnoBy using transaction functionsyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersyesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyes, with Range Indexes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoRole-based access control at the document and subdocument levelsyes, using Riak Security

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More resources
Apache ImpalaDatomicMarkLogicRiak KV
Conferences, events and webinars

Progress MarkLogic World
Washington DC, 23-25 September 2024

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