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DBMS > Apache Impala vs. GridDB vs. Linter vs. Weaviate

System Properties Comparison Apache Impala vs. GridDB vs. Linter vs. Weaviate

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonLinter  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataRDBMS for high security requirementsAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSTime Series DBMSRelational DBMSVector DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
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
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score1.52
Rank#153  Overall
#5  Vector DBMS
Websiteimpala.apache.orggriddb.netlinter.rugithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.netweaviate.io/­developers/­weaviate
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba Corporationrelex.ruWeaviate B.V.
Initial release2013201319902019
Current release4.1.0, June 20225.1, August 20221.19, May 2023
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 infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C and C++Go
Server operating systemsLinuxLinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesyesyesyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes infostring, int, float, geo point, date, cross reference, fuzzy references
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 indexesyesyesyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)yesGraphQL is used as query language
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoproprietary syntax with the possibility to convert from PL/SQLno
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replicationyes
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
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDno
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 KerberosAccess rights for users can be defined per databasefine grained access rights according to SQL-standardAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
Apache ImpalaGridDBLinterWeaviate
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
As a database supporting the development of generative AI and semantic search applications...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
All companies that have data. ​
» more
Market metricsGitHub trending repository
» more
As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
Apache ImpalaGridDBLinterWeaviate
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