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DBMS > Vertica vs. VictoriaMetrics vs. VoltDB

System Properties Comparison Vertica vs. VictoriaMetrics vs. VoltDB

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Editorial information provided by DB-Engines
NameVertica infoOpenText™ Vertica™  Xexclude from comparisonVictoriaMetrics  Xexclude from comparisonVoltDB  Xexclude from comparison
DescriptionCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.A 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 memory
Primary database modelRelational DBMS infoColumn orientedTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.06
Rank#42  Overall
#26  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Score1.47
Rank#157  Overall
#73  Relational DBMS
Websitewww.vertica.comvictoriametrics.comwww.voltdb.com
Technical documentationvertica.com/­documentationdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
docs.voltdb.com
DeveloperOpenText infopreviously Micro Focus and Hewlett PackardVictoriaMetricsVoltDB Inc.
Initial release200520182010
Current release12.0.3, January 2023v1.91, May 202311.3, April 2022
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache Version 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud serviceno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoJava, C++
Server operating systemsLinuxFreeBSD
Linux
macOS
OpenBSD
Linux
OS X infofor development
Data schemeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.noyes infoonly a subset of SQL 99
APIs and other access methodsADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresyes, PostgreSQL PL/pgSQL, with minor differencesnoJava
Triggersyes, called Custom Alertsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning, hierarchical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Synchronous replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infoBi-directional Spark integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashUsers and roles with access to stored procedures
More information provided by the system vendor
Vertica infoOpenText™ Vertica™VictoriaMetricsVoltDB
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Vertica infoOpenText™ Vertica™VictoriaMetricsVoltDB
Recent citations in the news

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 VoltDB Launches Active(N) Lossless Cross Data Center Replication
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VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Aims for Fast Big Data Development -- ADTmag
29 January 2015, ADT Magazine

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
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