DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Badger vs. Fujitsu Enterprise Postgres vs. Google Cloud Bigtable vs. InterSystems Caché

System Properties Comparison Badger vs. Fujitsu Enterprise Postgres vs. Google Cloud Bigtable vs. InterSystems Caché

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInterSystems Caché  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A multi-model DBMS and application server
Primary database modelKey-value storeRelational DBMSKey-value store
Wide column store
Key-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitegithub.com/­dgraph-io/­badgerwww.postgresql.fastware.comcloud.google.com/­bigtablewww.intersystems.com/­products/­cache
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.postgresql.fastware.com/­product-manualscloud.google.com/­bigtable/­docsdocs.intersystems.com
DeveloperDGraph LabsPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleInterSystems
Initial release201720151997
Current releaseFujitsu Enterprise Postgres 14, January 20222018.1.4, May 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercial
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 languageGoC
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
Windows
hostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freedepending on used data model
Typing infopredefined data types such as float or datenoyesnoyes
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.nonoyes
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyesnoyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
Server-side scripts infoStored proceduresnouser defined functionsnoyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnonepartitioning by range, list and by hashShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles
More information provided by the system vendor
BadgerFujitsu Enterprise PostgresGoogle Cloud BigtableInterSystems Caché
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
BadgerFujitsu Enterprise PostgresGoogle Cloud BigtableInterSystems Caché
Recent citations in the news

Fujitsu Develops Column-Oriented Data-Processing Engine Enabling Fast, High-Volume Data Analysis in Database ...
26 February 2015, Fujitsu

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

AWS, GCP, Oracle, Azure, SAP Lead Cloud DBMS Market: Gartner
12 February 2022, CRN

Announcing IBM Spectrum Sentinel: Building a Cyber Resilient Future
24 June 2022, ibm.com

Associative Data Modeling Demystified - Part1 - DataScienceCentral.com
9 July 2016, Data Science Central

Choosing a Database Technology. A roadmap and process overview | by Shirish Joshi
23 February 2020, Towards Data Science

Nearly three years on from Cambridge's Epic go-live
23 August 2017, Digital Health

provided by Google News



Share this page

Featured Products

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here