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DBMS > Apache Impala vs. GridGain vs. mSQL vs. Prometheus vs. Riak KV

System Properties Comparison Apache Impala vs. GridGain vs. mSQL vs. Prometheus vs. Riak KV

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridGain  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonPrometheus  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGridGain is an in-memory computing platform, built on Apache IgnitemSQL (Mini SQL) is a simple and lightweight RDBMSOpen-source Time Series DBMS and monitoring systemDistributed, fault tolerant key-value store
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSTime Series DBMSKey-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
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websiteimpala.apache.orgwww.gridgain.comhughestech.com.au/­products/­msqlprometheus.io
Technical documentationimpala.apache.org/­impala-docs.htmlwww.gridgain.com/­docs/­index.htmlprometheus.io/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGridGain Systems, Inc.Hughes TechnologiesOpenSource, formerly Basho Technologies
Initial release20132007199420152009
Current release4.1.0, June 2022GridGain 8.5.14.4, October 20213.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infofree licenses can be providedOpen Source infoApache 2.0Open Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, C++, .NetCGoErlang
Server operating systemsLinuxLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Windows
Linux
OS X
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesNumeric data onlyno
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.noyesnono infoImport of XML data possibleno
Secondary indexesyesyesyesnorestricted
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersnono
APIs and other access methodsJDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP/JSON APIHTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Delphi
Java
Perl
PHP
Tcl
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
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 (compute grid and cache interceptors can be used instead)nonoErlang
Triggersnoyes (cache interceptors and events)nonoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes (replicated cache)noneyes infoby Federationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)nonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencynonenoneEventual Consistency
Foreign keys infoReferential integritynonononono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesnoyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosSecurity Hooks for custom implementationsnonoyes, using Riak Security

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More resources
Apache ImpalaGridGainmSQL infoMini SQLPrometheusRiak KV
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