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DBMS > Databricks vs. etcd vs. HEAVY.AI vs. KeyDB

System Properties Comparison Databricks vs. etcd vs. HEAVY.AI vs. KeyDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKeyDB  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 distributed reliable key-value storeA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMSKey-value store
Secondary database modelsSpatial 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
Score7.25
Rank#54  Overall
#5  Key-value stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Websitewww.databricks.cometcd.io
github.com/­etcd-io/­etcd
github.com/­heavyai/­heavydb
www.heavy.ai
github.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.heavy.aidocs.keydb.dev
DeveloperDatabricksHEAVY.AI, Inc.EQ Alpha Technology Ltd.
Initial release201320162019
Current release3.4, August 20195.10, January 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoBSD-3
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 languageGoC++ and CUDAC++
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
LinuxLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or datenoyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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.yesnonono
Secondary indexesyesnonoyes infoby using the Redis Search module
SQL infoSupport of SQLwith Databricks SQLnoyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
JDBC
ODBC
Thrift
Vega
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesPython
R
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
All languages supporting JDBC/ODBC/Thrift
Python
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
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoLua
Triggersyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardsimple password-based access control and ACL
More information provided by the system vendor
DatabricksetcdHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KeyDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksetcdHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KeyDB
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