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DBMS > Apache Impala vs. GridDB vs. SAP HANA vs. Vitess

System Properties Comparison Apache Impala vs. GridDB vs. SAP HANA vs. Vitess

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonSAP HANA  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataIn-memory, column based data store. Available as appliance or cloud serviceScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
Document store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score44.27
Rank#23  Overall
#16  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteimpala.apache.orggriddb.netwww.sap.com/­products/­hana.htmlvitess.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.nethelp.sap.com/­hanavitess.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationSAPThe Linux Foundation, PlanetScale
Initial release2013201320102013
Current release4.1.0, June 20225.1, August 20222.0 SPS07 (April 4, 2023), April 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono infoalso available as a cloud based serviceno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Go
Server operating systemsLinuxLinuxAppliance or cloud-serviceDocker
Linux
macOS
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)yesyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoSQLScript, Ryes infoproprietary syntax
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseyesUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
Apache ImpalaGridDBSAP HANAVitess
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache ImpalaGridDBSAP HANAVitess
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