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DBMS > etcd vs. Fujitsu Enterprise Postgres vs. Google Cloud Firestore vs. LevelDB vs. Splice Machine

System Properties Comparison etcd vs. Fujitsu Enterprise Postgres vs. Google Cloud Firestore vs. LevelDB vs. Splice Machine

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonLevelDB  Xexclude from comparisonSplice Machine  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.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeRelational DBMSDocument storeKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.05
Rank#53  Overall
#5  Key-value stores
Score0.22
Rank#304  Overall
#137  Relational DBMS
Score6.63
Rank#54  Overall
#9  Document stores
Score2.33
Rank#111  Overall
#19  Key-value stores
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.postgresql.fastware.comfirebase.google.com/­products/­firestoregithub.com/­google/­leveldbsplicemachine.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.postgresql.fastware.com/­product-manualsfirebase.google.com/­docs/­firestoregithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsplicemachine.com/­how-it-works
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleGoogleSplice Machine
Initial release201720112014
Current release3.4, August 2019Fujitsu Enterprise Postgres 14, January 20221.23, February 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoBSDOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoCC++Java
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
Windows
hostedIllumos
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyesyesnoyes
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.nonono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLnoyesnonoyes
APIs and other access methodsgRPC
JSON over HTTP
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
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
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsyes, Firebase Rules & Cloud Functionsnoyes infoJava
Triggersyes, watching key changesyesyes, with Cloud Functionsnoyes
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
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 replicationMulti-source replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud DataflownoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.noAccess rights for users, groups and roles according to SQL-standard

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More resources
etcdFujitsu Enterprise PostgresGoogle Cloud FirestoreLevelDBSplice Machine
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