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DBMS > Apache Phoenix vs. etcd vs. Google Cloud Datastore vs. RDF4J

System Properties Comparison Apache Phoenix vs. etcd vs. Google Cloud Datastore vs. RDF4J

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA distributed reliable key-value storeAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSKey-value storeDocument storeRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Websitephoenix.apache.orgetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastorerdf4j.org
Technical documentationphoenix.apache.orgetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsrdf4j.org/­documentation
DeveloperApache Software FoundationGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release201420082004
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.4, August 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoJava
Server operating systemsLinux
Unix
Windows
FreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Unix
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesnoyes, details hereyes
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 indexesyesnoyesyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)no
APIs and other access methodsJDBCgRPC
JSON over HTTP
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnousing Google App Engineyes
Triggersnoyes, watching key changesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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Apache PhoenixetcdGoogle Cloud DatastoreRDF4J infoformerly known as Sesame
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