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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonVictoriaMetrics  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparisonYottaDB  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 solutionA general purpose database with bitemporal SQL and Datalog and graph queriesA fast and solid embedded Key-value store
Primary database modelRelational DBMSWide column storeTime Series DBMSDocument storeKey-value store
Secondary database modelsDocument storeRelational DBMS infousing the Octo plugin
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
Score0.13
Rank#330  Overall
#45  Document stores
Score0.21
Rank#309  Overall
#43  Key-value stores
Websiteimpala.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tablesvictoriametrics.comgithub.com/­xtdb/­xtdb
www.xtdb.com
yottadb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
www.xtdb.com/­docsyottadb.com/­resources/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftVictoriaMetricsJuxt Ltd.YottaDB, LLC
Initial release20132012201820192001
Current release4.1.0, June 2022v1.91, May 20231.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2.0Open Source infoMIT LicenseOpen Source infoAGPL 3.0
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++GoClojureC
Server operating systemsLinuxhostedFreeBSD
Linux
macOS
OpenBSD
All OS with a Java 8 (and higher) VM
Linux
Docker
Linux
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, extensible-data-notation formatno
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 indexesyesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnonolimited SQL, making use of Apache Calciteby using the Octo plugin
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIGraphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
HTTP REST
JDBC
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenone
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 replicationyes, each node contains all datayes
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
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
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 groups based on OS-security mechanisms

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More resources
Apache ImpalaMicrosoft Azure Table StorageVictoriaMetricsXTDB infoformerly named CruxYottaDB
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