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DBMS > Databricks vs. etcd vs. eXtremeDB vs. Fauna vs. Hive

System Properties Comparison Databricks vs. etcd vs. eXtremeDB vs. Fauna vs. Hive

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonetcd  Xexclude from comparisoneXtremeDB  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonHive  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 storeNatively in-memory DBMS with options for persistency, high-availability and clusteringFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.data warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMS
Time Series DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational 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
Score7.03
Rank#54  Overall
#5  Key-value stores
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Websitewww.databricks.cometcd.io
github.com/­etcd-io/­etcd
www.mcobject.comfauna.comhive.apache.org
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.mcobject.com/­docs/­extremedb.htmdocs.fauna.comcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperDatabricksMcObjectFauna, Inc.Apache Software Foundation infoinitially developed by Facebook
Initial release2013200120142012
Current release3.4, August 20198.2, 20213.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC and C++ScalaJava
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
AIX
HP-UX
Linux
macOS
Solaris
Windows
hostedAll OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesnoyes
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 infosupport of XML interfaces availableno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes infowith the option: eXtremeSQLnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Thrift
Supported programming languagesPython
R
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C
C#
C++
Java
Lua
Python
Scala
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyesuser defined functionsyes infouser defined functions and integration of map-reduce
Triggersyes, watching key changesyes infoby defining eventsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardinghorizontal partitioning infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Active Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Multi-source replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlnoIdentity management, authentication, and access controlAccess rights for users, groups and roles
More information provided by the system vendor
DatabricksetcdeXtremeDBFauna infopreviously named FaunaDBHive
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...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
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...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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DatabricksetcdeXtremeDBFauna infopreviously named FaunaDBHive
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