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DBMS > Prometheus vs. Spark SQL vs. Teradata vs. TigerGraph

System Properties Comparison Prometheus vs. Spark SQL vs. Teradata vs. TigerGraph

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Editorial information provided by DB-Engines
NamePrometheus  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionOpen-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelTime Series DBMSRelational DBMSRelational DBMSGraph DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial 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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websiteprometheus.iospark.apache.org/­sqlwww.teradata.comwww.tigergraph.com
Technical documentationprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.comdocs.tigergraph.com
DeveloperApache Software FoundationTeradata
Initial release2015201419842017
Current release3.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScalaC++
Server operating systemsLinux
Windows
Linux
OS X
Windows
hosted
Linux
Linux
Data schemeyesyesyesyes
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 possiblenoyesno
Secondary indexesnonoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infoSQL 2016 + extensionsSQL-like query language (GSQL)
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
C++
Java
Server-side scripts infoStored proceduresnonoyes infoUDFs, stored procedures, table functions in parallelyes
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby FederationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Foreign keys infoReferential integritynonoyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
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.nonoyesno
User concepts infoAccess controlnonofine grained access rights according to SQL-standardRole-based access control

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More resources
PrometheusSpark SQLTeradataTigerGraph
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