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DBMS > Badger vs. Faircom DB vs. Google Cloud Datastore vs. H2

System Properties Comparison Badger vs. Faircom DB vs. Google Cloud Datastore vs. H2

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonH2  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.
Primary database modelKey-value storeKey-value store
Relational DBMS
Document storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score8.33
Rank#46  Overall
#30  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.faircom.com/­products/­faircom-dbcloud.google.com/­datastorewww.h2database.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcloud.google.com/­datastore/­docswww.h2database.com/­html/­main.html
DeveloperDGraph LabsFairCom CorporationGoogleThomas Mueller
Initial release2017197920082005
Current releaseV12, November 20202.2.220, July 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infoRestricted, free version availablecommercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoANSI C, C++Java
Server operating systemsBSD
Linux
OS X
Solaris
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedAll OS with a Java VM
Data schemeschema-freeschema free, schema optional, schema required, partial schema,schema-freeyes
Typing infopredefined data types such as float or datenoyes, ANSI SQL Types, JSON, typed binary structuresyes, details hereyes
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.nononono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsSQL-like query language (GQL)yes
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesGo.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++using Google App EngineJava Stored Procedures and User-Defined Functions
TriggersnoyesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-source replication using PaxosWith clustering: 2 database servers on different computers operate on identical copies of a database
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
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.Immediate Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
BadgerFaircom DB infoformerly c-treeACEGoogle Cloud DatastoreH2
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