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DBMS > atoti vs. etcd vs. Google Cloud Datastore vs. RDF4J vs. searchxml

System Properties Comparison atoti vs. etcd vs. Google Cloud Datastore vs. RDF4J vs. searchxml

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonsearchxml  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.A 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.DBMS for structured and unstructured content wrapped with an application server
Primary database modelObject oriented DBMSKey-value storeDocument storeRDF storeNative XML DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented 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
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Websiteatoti.ioetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastorerdf4j.orgwww.searchxml.net/­category/­products
Technical documentationdocs.atoti.ioetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsrdf4j.org/­documentationwww.searchxml.net/­support/­handouts
DeveloperActiveViamGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.informationpartners gmbh
Initial release200820042015
Current release3.4, August 20191.0
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache Version 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
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 languageJavaGoJavaC++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Unix
Windows
Windows
Data schemeschema-freeschema-freeyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or datenoyes, details hereyesyes
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.nonoyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)noSQL-like query language (GQL)nono
APIs and other access methodsgRPC
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
RESTful HTTP API
WebDAV
XQuery
XSLT
Supported programming languages.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
C++ infomost other programming languages supported via APIs
Server-side scripts infoStored proceduresPythonnousing Google App Engineyesyes infoon the application server
Triggersyes, watching key changesCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication using Paxosnoneyes infosychronisation to multiple collections
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API usedmultiple readers, single writer
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noDomain, group and role-based access control at the document level and for application services

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More resources
atotietcdGoogle Cloud DatastoreRDF4J infoformerly known as Sesamesearchxml
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