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DBMS > etcd vs. Rockset vs. Spark SQL vs. Yanza

System Properties Comparison etcd vs. Rockset vs. Spark SQL vs. Yanza

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA distributed reliable key-value storeA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS for IoT Applications
Primary database modelKey-value storeDocument storeRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score0.82
Rank#212  Overall
#36  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
rockset.comspark.apache.org/­sqlyanza.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperRocksetApache Software FoundationYanza
Initial release201920142015
Current release3.4, August 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenoyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++Scala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Windows
Windows
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenodynamic typingyesno
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 infoingestion from XML files supportednono
Secondary indexesnoall fields are automatically indexednono
SQL infoSupport of SQLnoRead-only SQL queries, including JOINsSQL-like DML and DDL statementsno
APIs and other access methodsgRPC
JSON over HTTP
HTTP RESTJDBC
ODBC
HTTP API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresnononono
Triggersyes, watching key changesnonoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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 and organizations can be defined via Rockset consolenono

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More resources
etcdRocksetSpark SQLYanza
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