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DBMS > etcd vs. Fujitsu Enterprise Postgres vs. RocksDB vs. Spark SQL vs. TerarkDB

System Properties Comparison etcd vs. Fujitsu Enterprise Postgres vs. RocksDB vs. Spark SQL vs. TerarkDB

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonRocksDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionA distributed reliable key-value storeEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Embeddable persistent key-value store optimized for fast storage (flash and RAM)Spark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelKey-value storeRelational DBMSKey-value storeRelational DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score3.65
Rank#85  Overall
#11  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteetcd.io
github.com/­etcd-io/­etcd
www.postgresql.fastware.comrocksdb.orgspark.apache.org/­sqlgithub.com/­bytedance/­terarkdb
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.postgresql.fastware.com/­product-manualsgithub.com/­facebook/­rocksdb/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyFacebook, Inc.Apache Software FoundationByteDance, originally Terark
Initial release201320142016
Current release3.4, August 2019Fujitsu Enterprise Postgres 14, January 20228.11.4, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoBSDOpen Source infoApache 2.0commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoCC++ScalaC++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesnoyesno
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 indexesnoyesnonono
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statementsno
APIs and other access methodsgRPC
JSON over HTTP
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
C++ API
Java API
JDBC
ODBC
C++ API
Java API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
Perl
Python
Ruby
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnouser defined functionsnonono
Triggersyes, watching key changesyesnono
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashhorizontal partitioningyes, 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.Source-replica replicationyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesnono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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.noyesnoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardnonono
More information provided by the system vendor
etcdFujitsu Enterprise PostgresRocksDBSpark SQLTerarkDB
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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Related products and services
3rd partiesSpeedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
» more

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More resources
etcdFujitsu Enterprise PostgresRocksDBSpark SQLTerarkDB
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