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DBMS > Apache Impala vs. BaseX vs. GridDB vs. Warp 10

System Properties Comparison Apache Impala vs. BaseX vs. GridDB vs. Warp 10

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBaseX  Xexclude from comparisonGridDB  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Scalable in-memory time series database optimized for IoT and Big DataTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSNative XML DBMSTime Series DBMSTime Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.84
Rank#135  Overall
#4  Native XML DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websiteimpala.apache.orgbasex.orggriddb.netwww.warp10.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.basex.orgdocs.griddb.netwww.warp10.io/­content/­02_Getting_started
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBaseX GmbHToshiba CorporationSenX
Initial release2013200720132015
Current release4.1.0, June 202211.0, June 20245.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSD licenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache License 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++JavaC++Java
Server operating systemsLinuxLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesno infoXQuery supports typesyes infonumerical, string, blob, geometry, boolean, timestampyes
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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP API
Jupyter
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBCActionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnoyes infoWarpScript
Triggersnoyes infovia eventsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanomultiple readers, single writerACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization concept on 4 levelsAccess rights for users can be defined per databaseMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
Apache ImpalaBaseXGridDBWarp 10
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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More resources
Apache ImpalaBaseXGridDBWarp 10
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