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DBMS > Google BigQuery vs. Graph Engine vs. jBASE vs. PouchDB vs. YTsaurus

System Properties Comparison Google BigQuery vs. Graph Engine vs. jBASE vs. PouchDB vs. YTsaurus

Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonjBASE  Xexclude from comparisonPouchDB  Xexclude from comparisonYTsaurus  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA robust multi-value DBMS comprising development tools and middlewareJavaScript DBMS with an API inspired by CouchDBYTsaurus is an open source platform for distributed storage and processing.
Primary database modelRelational DBMSGraph DBMS
Key-value store
Multivalue DBMSDocument storeDocument store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score0.11
Rank#340  Overall
#45  Document stores
#50  Key-value stores
Websitecloud.google.com/­bigquerywww.graphengine.iowww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasepouchdb.comytsaurus.tech
Technical documentationcloud.google.com/­bigquery/­docswww.graphengine.io/­docs/­manualdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9pouchdb.com/­guidesytsaurus.tech/­docs/­en
DeveloperGoogleMicrosoftRocket Software (formerly Zumasys)Apache Software FoundationYandex
Initial release20102010199120122023
Current release5.77.1.1, June 2019
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen SourceOpen Source infoApache License, Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CJavaScriptC++
Server operating systemshosted.NETAIX
Linux
Windows
server-less, requires a JavaScript environment (browser, Node.js)Ubuntu
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesoptionalnoyes
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.nonoyesnono
Secondary indexesnoyes infovia views
SQL infoSupport of SQLyesnoEmbedded SQL for jBASE in BASICnoYQL, an SQL-based language, is supported
APIs and other access methodsRESTful HTTP/JSON APIRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C#
C++
F#
Visual Basic
.Net
Basic
Jabbascript
Java
JavaScriptC++
Go
Java
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyesyesView functions in JavaScript
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningShardingSharding infowith a proxy-based framework, named couchdb-loungeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights can be defined down to the item levelnoAccess Control Lists

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More resources
Google BigQueryGraph Engine infoformer name: TrinityjBASEPouchDBYTsaurus
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