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DBMS > Google Cloud Bigtable vs. JanusGraph vs. Microsoft Azure SQL Database vs. Solr

System Properties Comparison Google Cloud Bigtable vs. JanusGraph vs. Microsoft Azure SQL Database vs. Solr

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Database as a Service offering with high compatibility to Microsoft SQL ServerA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value store
Wide column store
Graph DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitecloud.google.com/­bigtablejanusgraph.orgazure.microsoft.com/­en-us/­products/­azure-sql/­databasesolr.apache.org
Technical documentationcloud.google.com/­bigtable/­docsdocs.janusgraph.orgdocs.microsoft.com/­en-us/­azure/­azure-sqlsolr.apache.org/­resources.html
DeveloperGoogleLinux Foundation; originally developed as Titan by AureliusMicrosoftApache Software Foundation
Initial release2015201720102006
Current release0.6.3, February 2023V129.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java
Server operating systemshostedLinux
OS X
Unix
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or datenoyesyesyes 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 indexesnoyesyesyes 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)
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Clojure
Java
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyesTransact SQLJava plugins
Triggersnoyesyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesyes, with always 3 replicas availableyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia Faunus, a graph analytics enginenospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)User authentification and security via Rexster Graph Serverfine grained access rights according to SQL-standardyes

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More resources
Google Cloud BigtableJanusGraph infosuccessor of TitanMicrosoft Azure SQL Database infoformerly SQL AzureSolr
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