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DBMS > Prometheus vs. Tigris vs. Vertica vs. Yaacomo

System Properties Comparison Prometheus vs. Tigris vs. Vertica vs. Yaacomo

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Editorial information provided by DB-Engines
NamePrometheus  Xexclude from comparisonTigris  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionOpen-source Time Series DBMS and monitoring systemA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructureCloud 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.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelTime Series DBMSDocument store
Key-value store
Search engine
Time Series DBMS
Relational DBMS infoColumn orientedRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteprometheus.iowww.tigrisdata.comwww.vertica.comyaacomo.com
Technical documentationprometheus.io/­docswww.tigrisdata.com/­docsvertica.com/­documentation
DeveloperTigris Data, Inc.OpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release2015202220052009
Current release12.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0commercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++
Server operating systemsLinux
Windows
Linux
macOS
Windows
LinuxAndroid
Linux
Windows
Data schemeyesyesYes, 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 dateNumeric data onlyyesyesyes
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.no infoImport of XML data possiblenonono
Secondary indexesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methodsRESTful HTTP/JSON APICLI Client
gRPC
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languages.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Go
Java
JavaScript (Node.js)
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby FederationyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using FoundationDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnoAccess rights for users and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashfine grained access rights according to SQL-standard
More information provided by the system vendor
PrometheusTigrisVertica infoOpenText™ Vertica™Yaacomo
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...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
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...
» more

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More resources
PrometheusTigrisVertica infoOpenText™ Vertica™Yaacomo
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