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DBMS > Badger vs. Google Cloud Datastore vs. Informix vs. Lovefield

System Properties Comparison Badger vs. Google Cloud Datastore vs. Informix vs. Lovefield

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInformix  Xexclude from comparisonLovefield  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataEmbeddable relational database for web apps written in pure JavaScript
Primary database modelKey-value storeDocument storeRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score0.33
Rank#286  Overall
#131  Relational DBMS
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­datastorewww.ibm.com/­products/­informixgoogle.github.io/­lovefield
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­datastore/­docsinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
github.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperDGraph LabsGoogleIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Google
Initial release2017200819842014
Current release14.10.FC5, November 20202.1.12, February 2017
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infofree developer edition availableOpen Source infoApache 2.0
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 languageGoC, C++ and JavaJavaScript
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedAIX
HP-UX
Linux
macOS
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safari
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes, details hereyes infoSince Version 12.10 support for JSON/BSON datatypesyes
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.nonono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yesSQL-like query language infovia JavaScript builder pattern
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Supported programming languagesGo.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresnousing Google App Engineyesno
TriggersnoCallbacks using the Google Apps EngineyesUsing read-only observers
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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 pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Database
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infousing MemoryDB
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authentication, authorization, and auditing controlsno

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More resources
BadgerGoogle Cloud DatastoreInformixLovefield
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