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DBMS > Blueflood vs. Google Cloud Datastore vs. InfluxDB vs. Oracle Berkeley DB

System Properties Comparison Blueflood vs. Google Cloud Datastore vs. InfluxDB vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfluxDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for storing time series, events and metricsWidely used in-process key-value store
Primary database modelTime Series DBMSDocument storeTime Series DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#353  Overall
#33  Time Series DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score26.56
Rank#28  Overall
#1  Time Series DBMS
Score2.52
Rank#114  Overall
#20  Key-value stores
#3  Native XML DBMS
Websiteblueflood.iocloud.google.com/­datastorewww.influxdata.com/­products/­influxdb-overviewwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationgithub.com/­rax-maas/­blueflood/­wikicloud.google.com/­datastore/­docsdocs.influxdata.com/­influxdbdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperRackspaceGoogleOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2013200820131994
Current release2.7.5, January 202418.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsLinux
OS X
hostedLinux
OS X infothrough Homebrew
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemepredefined schemeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, details hereNumeric data and Stringsno
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.nononoyes infoonly with the Berkeley DB XML edition
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languageyes infoSQL interfaced based on SQLite is available
APIs and other access methodsHTTP RESTgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JSON over UDP
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresnousing Google App Enginenono
TriggersnoCallbacks using the Google Apps Enginenoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingSharding infoin enterprise version onlynone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraMulti-source replication using Paxosselectable replication factor infoin enterprise version onlySource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
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 integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoDepending on used storage engineyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple rights management via user accountsno
More information provided by the system vendor
BluefloodGoogle Cloud DatastoreInfluxDBOracle Berkeley DB
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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More resources
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