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DBMS > Apache Impala vs. Graph Engine vs. H2GIS vs. Microsoft Azure Table Storage vs. Riak KV

System Properties Comparison Apache Impala vs. Graph Engine vs. H2GIS vs. Microsoft Azure Table Storage vs. Riak KV

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonH2GIS  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineSpatial extension of H2A Wide Column Store for rapid development using massive semi-structured datasetsDistributed, fault tolerant key-value store
Primary database modelRelational DBMSGraph DBMS
Key-value store
Spatial DBMSWide column storeKey-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.00
Rank#383  Overall
#7  Spatial DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score4.10
Rank#82  Overall
#9  Key-value stores
Websiteimpala.apache.orgwww.graphengine.iowww.h2gis.orgazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationimpala.apache.org/­impala-docs.htmlwww.graphengine.io/­docs/­manualwww.h2gis.org/­docs/­homewww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftCNRSMicrosoftOpenSource, formerly Basho Technologies
Initial release20132010201320122009
Current release4.1.0, June 20223.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMIT LicenseOpen Source infoLGPL 3.0commercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++.NET and CJavaErlang
Server operating systemsLinux.NEThostedLinux
OS X
Data schemeyesyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nonononono
Secondary indexesyesyesnorestricted
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIRESTful HTTP APIHTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
F#
Visual Basic
Java.Net
C#
C++
Java
JavaScript (Node.js)
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-reduceyesyes infobased on H2noErlang
Triggersnonoyesnoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningnoneSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infobased on H2yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesnono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes infobased on H2Access rights based on private key authentication or shared access signaturesyes, using Riak Security

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More resources
Apache ImpalaGraph Engine infoformer name: TrinityH2GISMicrosoft Azure Table StorageRiak KV
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