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DBMS > Databricks vs. PostGIS vs. SurrealDB vs. WakandaDB

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonPostGIS  Xexclude from comparisonSurrealDB  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 fully ACID transactional, developer-friendly, multi-model DBMSWakandaDB 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 DBMSDocument store
Graph DBMS
Object 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
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.databricks.compostgis.netsurrealdb.comwakanda.github.io
Technical documentationdocs.databricks.compostgis.net/­documentationsurrealdb.com/­docswakanda.github.io/­doc
DeveloperDatabricksSurrealDB LtdWakanda SAS
Initial release2013200520222012
Current release3.4.2, February 2024v1.1.1, January 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoGPL v2.0Open SourceOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCRustC++, JavaScript
Server operating systemshostedLinux
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 dateyesyesyes
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.yesyesno
Secondary indexesyesyes
SQL infoSupport of SQLwith Databricks SQLyesSQL-like query languageno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
GraphQL
RESTful HTTP API
WebSocket
RESTful HTTP API
Supported programming languagesPython
R
Scala
Deno
Go
JavaScript (Node.js)
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 PostgreSQLnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infobased on PostgreSQLnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
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.nonono
User concepts infoAccess controlyes infobased on PostgreSQLyes, based on authentication and database rulesyes
More information provided by the system vendor
DatabricksPostGISSurrealDBWakandaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksPostGISSurrealDBWakandaDB
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