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DBMS > Apache Impala vs. GridDB vs. Microsoft Azure Table Storage vs. VictoriaMetrics vs. XTDB

System Properties Comparison Apache Impala vs. GridDB vs. Microsoft Azure Table Storage vs. VictoriaMetrics vs. XTDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonVictoriaMetrics  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataA Wide Column Store for rapid development using massive semi-structured datasetsA fast, cost-effective and scalable Time Series DBMS and monitoring solutionA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSTime Series DBMSWide column storeTime Series DBMSDocument store
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score3.55
Rank#80  Overall
#6  Wide column stores
Score1.23
Rank#165  Overall
#15  Time Series DBMS
Score0.13
Rank#330  Overall
#45  Document stores
Websiteimpala.apache.orggriddb.netazure.microsoft.com/­en-us/­services/­storage/­tablesvictoriametrics.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.netdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
www.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationMicrosoftVictoriaMetricsJuxt Ltd.
Initial release20132013201220182019
Current release4.1.0, June 20225.1, August 2022v1.91, May 20231.19, September 2021
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 2.0Open Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++GoClojure
Server operating systemsLinuxLinuxhostedFreeBSD
Linux
macOS
OpenBSD
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes, extensible-data-notation format
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.nonononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)nonolimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP APIGraphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
HTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenononono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Synchronous replicationyes, each node contains all data
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 jobsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container leveloptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseAccess rights based on private key authentication or shared access signatures

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More resources
Apache ImpalaGridDBMicrosoft Azure Table StorageVictoriaMetricsXTDB infoformerly named Crux
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