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DBMS > etcd vs. Firebolt vs. Hive vs. Spark SQL

System Properties Comparison etcd vs. Firebolt vs. Hive vs. Spark SQL

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonFirebolt  Xexclude from comparisonHive  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed reliable key-value storeHighly scalable cloud data warehouse and analytics product infoForked from Clickhousedata warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score1.73
Rank#140  Overall
#63  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.firebolt.iohive.apache.orgspark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.firebolt.iocwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFirebolt Analytics Inc.Apache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release202020122014
Current release3.4, August 20193.1.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaScala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedAll OS with a Java VMLinux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
.Net
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Go
JavaScript (Node.js)
Python
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infouser defined functions and integration of map-reduceno
Triggersyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.depending on storage layerselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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.nono
User concepts infoAccess controlnoAccess rights for users, groups and rolesno

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More resources
etcdFireboltHiveSpark SQL
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