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DBMS > Prometheus vs. Splice Machine vs. TinkerGraph vs. Vertica

System Properties Comparison Prometheus vs. Splice Machine vs. TinkerGraph vs. Vertica

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Editorial information provided by DB-Engines
NamePrometheus  Xexclude from comparisonSplice Machine  Xexclude from comparisonTinkerGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionOpen-source Time Series DBMS and monitoring systemOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 APICloud 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
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.13
Rank#345  Overall
#35  Graph DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteprometheus.iosplicemachine.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlinwww.vertica.com
Technical documentationprometheus.io/­docssplicemachine.com/­how-it-worksvertica.com/­documentation
DeveloperSplice MachineOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201420092005
Current release3.1, March 202112.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0commercial 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

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Implementation languageGoJavaJavaC++
Server operating systemsLinux
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesschema-freeYes, 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 possiblenono
Secondary indexesnoyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyesnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP/JSON APIJDBC
Native Spark Datasource
ODBC
TinkerPop 3ADO.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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Groovy
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infoJavanoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioningnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby FederationMulti-source replication
Source-replica replication
noneMulti-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 methodsnoYes, via Full Spark Integrationnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynoyesyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)noyes
Durability infoSupport for making data persistentyesyesoptionalyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
PrometheusSplice MachineTinkerGraphVertica infoOpenText™ Vertica™
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
PrometheusSplice MachineTinkerGraphVertica infoOpenText™ Vertica™
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