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DBMS > BigObject vs. Brytlyt vs. Ehcache vs. Google Cloud Datastore

System Properties Comparison BigObject vs. Brytlyt vs. Ehcache vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonBrytlyt  Xexclude from comparisonEhcache  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLA widely adopted Java cache with tiered storage optionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSKey-value storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score4.89
Rank#67  Overall
#8  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Websitebigobject.iobrytlyt.iowww.ehcache.orgcloud.google.com/­datastore
Technical documentationdocs.bigobject.iodocs.brytlyt.iowww.ehcache.org/­documentationcloud.google.com/­datastore/­docs
DeveloperBigObject, Inc.BrytlytTerracotta Inc, owned by Software AGGoogle
Initial release2015201620092008
Current release5.0, August 20233.10.0, March 2022
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAJava
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
Windows
All OS with a Java VMhosted
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, details here
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoSQL-like query language (GQL)
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCachegRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Java.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresLuauser defined functions infoin PL/pgSQLnousing Google App Engine
Triggersnoyesyes infoCache Event ListenersCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoby using Terracotta ServerSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationyes infoby using Terracotta ServerMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate 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 integrityyes infoautomatically between fact table and dimension tablesyesnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyes infosupports JTA and can work as an XA resourceACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyes infousing a tiered cache-storage approachyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
BigObjectBrytlytEhcacheGoogle Cloud Datastore
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