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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonVictoriaMetrics  Xexclude from comparisonVoltDB  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA Wide Column Store for rapid development using massive semi-structured datasetsA fast, cost-effective and scalable Time Series DBMS and monitoring solutionDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memoryA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSWide column storeTime Series DBMSRelational DBMSDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score3.55
Rank#80  Overall
#6  Wide column stores
Score1.23
Rank#165  Overall
#15  Time Series DBMS
Score1.38
Rank#156  Overall
#72  Relational DBMS
Score0.13
Rank#330  Overall
#45  Document stores
Websiteimpala.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tablesvictoriametrics.comwww.voltdb.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
docs.voltdb.comwww.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftVictoriaMetricsVoltDB Inc.Juxt Ltd.
Initial release20132012201820102019
Current release4.1.0, June 2022v1.91, May 202311.3, April 20221.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro EditionsOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoJava, C++Clojure
Server operating systemsLinuxhostedFreeBSD
Linux
macOS
OpenBSD
Linux
OS X infofor development
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, 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.nononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infoonly a subset of SQL 99limited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIGraphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Java API
JDBC
RESTful HTTP/JSON API
HTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Clojure
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoJavano
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Synchronous replicationMulti-source replication
Source-replica replication
yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono infoFOREIGN KEY constraints are not supportedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnoACID infoTransactions are executed single-threaded within stored proceduresACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the serveryes
Durability infoSupport for making data persistentyesyesyesyes infoSnapshots and command loggingyes, 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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights based on private key authentication or shared access signaturesUsers and roles with access to stored procedures

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More resources
Apache ImpalaMicrosoft Azure Table StorageVictoriaMetricsVoltDBXTDB infoformerly named Crux
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