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DBMS > Badger vs. Google Cloud Bigtable vs. InterSystems Caché vs. Solr

System Properties Comparison Badger vs. Google Cloud Bigtable vs. InterSystems Caché vs. Solr

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSolr  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.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 serverA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value storeKey-value store
Wide column store
Key-value store
Object oriented DBMS
Relational DBMS
Search engine
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­bigtablewww.intersystems.com/­products/­cachesolr.apache.org
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­bigtable/­docsdocs.intersystems.comsolr.apache.org/­resources.html
DeveloperDGraph LabsGoogleInterSystemsApache Software Foundation
Initial release2017201519972006
Current release2018.1.4, May 20209.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2
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 languageGoJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freedepending on used data modelyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or datenonoyesyes infosupports customizable data types and automatic typing
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.nonoyesyes
Secondary indexesnonoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnonoyesSolr Parallel SQL Interface
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesGoC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonoyesJava plugins
Triggersnonoyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesyes

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More resources
BadgerGoogle Cloud BigtableInterSystems CachéSolr
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