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DBMS > Prometheus vs. Sadas Engine vs. TigerGraph vs. Vertica

System Properties Comparison Prometheus vs. Sadas Engine vs. TigerGraph vs. Vertica

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Editorial information provided by DB-Engines
NamePrometheus  Xexclude from comparisonSadas Engine  Xexclude from comparisonTigerGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionOpen-source Time Series DBMS and monitoring systemSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeCloud 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.
Primary database modelTime Series DBMSRelational DBMSGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.92
Rank#51  Overall
#2  Time Series DBMS
Score0.03
Rank#379  Overall
#156  Relational DBMS
Score1.83
Rank#141  Overall
#13  Graph DBMS
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websiteprometheus.iowww.sadasengine.comwww.tigergraph.comwww.vertica.com
Technical documentationprometheus.io/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.tigergraph.comvertica.com/­documentation
DeveloperSADAS s.r.l.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015200620172005
Current release8.012.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infofree trial version availablecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++C++C++
Server operating systemsLinux
Windows
AIX
Linux
Windows
LinuxLinux
Data schemeyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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.
SQL infoSupport of SQLnoyesSQL-like query language (GSQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
Proprietary protocol
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
C++
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby FederationnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infomanaged by 'Learn by Usage'nono
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
PrometheusSadas EngineTigerGraphVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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
PrometheusSadas EngineTigerGraphVertica infoOpenText™ Vertica™
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