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DBMS > etcd vs. LevelDB vs. RisingWave vs. Spark SQL

System Properties Comparison etcd vs. LevelDB vs. RisingWave vs. Spark SQL

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonLevelDB  Xexclude from comparisonRisingWave  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed reliable key-value storeEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesA distributed RDBMS for stream processing, wire-compatible with PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.58
Rank#242  Overall
#111  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
github.com/­google/­leveldbwww.risingwave.com/­databasespark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
github.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.risingwave.com/­docs/­current/­introspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleRisingWave LabsApache Software Foundation
Initial release201120222014
Current release3.4, August 20191.23, February 20211.2, September 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSDOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++RustScala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Illumos
Linux
OS X
Windows
Docker
Linux
macOS
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenonoStandard SQL-types and JSONyes
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.nononono
Secondary indexesnonoyesno
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoUDFs in Python or Javano
Triggersyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, 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.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 datayesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnonoUsers and Rolesno

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More resources
etcdLevelDBRisingWaveSpark SQL
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