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DBMS > Brytlyt vs. Google Cloud Spanner vs. PouchDB vs. Spark SQL

System Properties Comparison Brytlyt vs. Google Cloud Spanner vs. PouchDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonPouchDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.JavaScript DBMS with an API inspired by CouchDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.33
Rank#269  Overall
#125  Relational DBMS
Score3.68
Rank#92  Overall
#48  Relational DBMS
Score3.09
Rank#98  Overall
#18  Document stores
Score22.86
Rank#35  Overall
#21  Relational DBMS
Websitewww.brytlyt.comcloud.google.com/­spannerpouchdb.comspark.apache.org/­sql
Technical documentationcloud.google.com/­spanner/­docspouchdb.com/­guidesspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBrytlytGoogleApache Software FoundationApache Software Foundation
Initial release2016201720122014
Current release0.9, October 20167.1.1, June 20193.2.0, October 2021
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and CUDAJavaScriptScala
Server operating systemsLinux
OS X
Windows
hostedserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.yes infospecific XML-type available, but no XML query functionality.nonono
Secondary indexesyesyesyes infovia viewsno
SQL infoSupport of SQLyesyes infoQuery statements complying to ANSI 2011noSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Go
Java
JavaScript (Node.js)
Python
JavaScriptJava
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLnoView functions in JavaScriptno
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infowith a proxy-based framework, named couchdb-loungeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication with 3 replicas for regional instances.Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes 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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
BrytlytGoogle Cloud SpannerPouchDBSpark SQL
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