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DBMS > Databricks vs. PostGIS vs. Qdrant vs. WakandaDB

System Properties Comparison Databricks vs. PostGIS vs. Qdrant vs. WakandaDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonPostGIS  Xexclude from comparisonQdrant  Xexclude from comparisonWakandaDB  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.Spatial extension of PostgreSQLA high-performance vector database with neural network or semantic-based matchingWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Relational DBMS
Spatial DBMSVector DBMSObject oriented DBMS
Secondary database modelsRelational 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
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.databricks.compostgis.netgithub.com/­qdrant/­qdrant
qdrant.tech
wakanda.github.io
Technical documentationdocs.databricks.compostgis.net/­documentationqdrant.tech/­documentationwakanda.github.io/­doc
DeveloperDatabricksQdrantWakanda SAS
Initial release2013200520212012
Current release3.4.2, February 20242.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoGPL v2.0Open Source infoApache Version 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCRustC++, JavaScript
Server operating systemshostedDocker
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesNumbers, Strings, Geo, Booleanyes
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.yesyesnono
Secondary indexesyesyesyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLwith Databricks SQLyesnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsyes
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodesyes infobased on PostgreSQLShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infobased on PostgreSQLCollection-level replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency, tunable consistencyImmediate Consistency
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
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 controlyes infobased on PostgreSQLKey-based authenticationyes
More information provided by the system vendor
DatabricksPostGISQdrantWakandaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksPostGISQdrantWakandaDB
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