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DBMS > Databricks vs. eXtremeDB vs. KeyDB vs. WakandaDB

System Properties Comparison Databricks vs. eXtremeDB vs. KeyDB vs. WakandaDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisoneXtremeDB  Xexclude from comparisonKeyDB  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.Natively in-memory DBMS with options for persistency, high-availability and clusteringAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsWakandaDB 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
Relational DBMS
Time Series 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
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score0.70
Rank#229  Overall
#32  Key-value stores
Score0.10
Rank#356  Overall
#17  Object oriented DBMS
Websitewww.databricks.comwww.mcobject.comgithub.com/­Snapchat/­KeyDB
keydb.dev
wakanda.github.io
Technical documentationdocs.databricks.comwww.mcobject.com/­docs/­extremedb.htmdocs.keydb.devwakanda.github.io/­doc
DeveloperDatabricksMcObjectEQ Alpha Technology Ltd.Wakanda SAS
Initial release2013200120192012
Current release8.2, 20212.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-3Open 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 languageC and C++C++C++, JavaScript
Server operating systemshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
LinuxLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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.yesno infosupport of XML interfaces availablenono
Secondary indexesyesyesyes infoby using the Redis Search module
SQL infoSupport of SQLwith Databricks SQLyes infowith the option: eXtremeSQLnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocoRESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesLuayes
Triggersyes infoby defining eventsnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDOptimistic locking, atomic execution of commands blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlsimple password-based access control and ACLyes
More information provided by the system vendor
DatabrickseXtremeDBKeyDBWakandaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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More resources
DatabrickseXtremeDBKeyDBWakandaDB
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