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DBMS > Apache Impala vs. GridDB vs. Lovefield vs. OrientDB

System Properties Comparison Apache Impala vs. GridDB vs. Lovefield vs. OrientDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonLovefield  Xexclude from comparisonOrientDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataEmbeddable relational database for web apps written in pure JavaScriptMulti-model DBMS (Document, Graph, Key/Value)
Primary database modelRelational DBMSTime Series DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Websiteimpala.apache.orggriddb.netgoogle.github.io/­lovefieldorientdb.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.netgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdwww.orientdb.com/­docs/­last/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationGoogleOrientDB LTD; CallidusCloud; SAP
Initial release2013201320142010
Current release4.1.0, June 20225.1, August 20222.1.12, February 20173.2.29, March 2024
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 availableOpen Source infoApache 2.0Open Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++JavaScriptJava
Server operating systemsLinuxLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariAll OS with a Java JDK (>= JDK 6)
Data schemeyesyesyesschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")
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.nononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language infovia JavaScript builder patternSQL-like query language, no joins
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaScript.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoJava, Javascript
TriggersnoyesUsing read-only observersHooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnoneMulti-source 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 infocould be achieved with distributed queries
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynonoyesyes inforelationship in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDB
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databasenoAccess rights for users and roles; record level security configurable
More information provided by the system vendor
Apache ImpalaGridDBLovefieldOrientDB
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 ImpalaGridDBLovefieldOrientDB
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