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DBMS > Apache Impala vs. BaseX vs. Cloudflare Workers KV vs. GridDB vs. Kyligence Enterprise

System Properties Comparison Apache Impala vs. BaseX vs. Cloudflare Workers KV vs. GridDB vs. Kyligence Enterprise

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBaseX  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonGridDB  Xexclude from comparisonKyligence Enterprise  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Scalable in-memory time series database optimized for IoT and Big DataA distributed analytics engine for big data, built on top of Apache Kylin
Primary database modelRelational DBMSNative XML DBMSKey-value storeTime Series DBMSRelational DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.73
Rank#142  Overall
#4  Native XML DBMS
Score0.32
Rank#283  Overall
#40  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.40
Rank#269  Overall
#124  Relational DBMS
Websiteimpala.apache.orgbasex.orgwww.cloudflare.com/­developer-platform/­workers-kvgriddb.netkyligence.io/­kyligence-enterprise
Technical documentationimpala.apache.org/­impala-docs.htmldocs.basex.orgdevelopers.cloudflare.com/­kv/­apidocs.griddb.net
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBaseX GmbHCloudflareToshiba CorporationKyligence, Inc.
Initial release20132007201820132016
Current release4.1.0, June 202210.7, August 20235.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSD licensecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++Java
Server operating systemsLinuxLinux
OS X
Windows
hostedLinuxLinux
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesno infoXQuery supports typesnoyes 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.nononono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL92, SQL-like TQL (Toshiba Query Language)ANSI SQL for queries (using Apache Calcite)
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
HTTP REST
Proprietary protocol
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
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++
Dart
JavaScript
Kotlin
Python
Rust
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnono
Triggersnoyes infovia eventsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanomultiple readers, single writernoACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyesno
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 database
More information provided by the system vendor
Apache ImpalaBaseXCloudflare Workers KVGridDBKyligence Enterprise
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 ImpalaBaseXCloudflare Workers KVGridDBKyligence Enterprise
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