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DBMS > Databricks vs. Pinecone vs. Prometheus vs. Quasardb

System Properties Comparison Databricks vs. Pinecone vs. Prometheus vs. Quasardb

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonPinecone  Xexclude from comparisonPrometheus  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A managed, cloud-native vector databaseOpen-source Time Series DBMS and monitoring systemDistributed, high-performance timeseries database
Primary database modelDocument store
Relational DBMS
Vector DBMSTime Series DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitewww.databricks.comwww.pinecone.ioprometheus.ioquasar.ai
Technical documentationdocs.databricks.comdocs.pinecone.io/­docs/­overviewprometheus.io/­docsdoc.quasar.ai/­master
DeveloperDatabricksPinecone Systems, Incquasardb
Initial release2013201920152009
Current release3.14.1, January 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++
Server operating systemshostedhostedLinux
Windows
BSD
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateString, Number, BooleanNumeric data onlyyes infointeger and binary
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.yesnono infoImport of XML data possibleno
Secondary indexesyesnoyes infowith tags
SQL infoSupport of SQLwith Databricks SQLnonoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIRESTful HTTP/JSON APIHTTP API
Supported programming languagesPython
R
Scala
Python.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby FederationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes infoTransient mode
User concepts infoAccess controlnoCryptographically strong user authentication and audit trail
More information provided by the system vendor
DatabricksPineconePrometheusQuasardb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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