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DBMS > Databricks vs. Speedb vs. WakandaDB

System Properties Comparison Databricks vs. Speedb vs. WakandaDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonSpeedb  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.An embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDBWakandaDB 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
Key-value storeObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.26
Rank#310  Overall
#45  Key-value stores
Score0.10
Rank#356  Overall
#17  Object oriented DBMS
Websitewww.databricks.comwww.speedb.iowakanda.github.io
Technical documentationdocs.databricks.comwakanda.github.io/­doc
DeveloperDatabricksSpeedbWakanda SAS
Initial release201320202012
Current release2.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0; commercial license availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, JavaScript
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or datenoyes
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
Secondary indexesyesno
SQL infoSupport of SQLwith Databricks SQLnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesPython
R
Scala
C
C++
Go
Java
Perl
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes
Triggersyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnoyes
More information provided by the system vendor
DatabricksSpeedbWakandaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Speedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more
Competitive advantagesSpeedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» more
Licensing and pricing modelsOpen source - Speedb OSS is released under an Apache license and can be found on...
» more

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DatabricksSpeedbWakandaDB
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