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DBMS > Google Cloud Bigtable vs. Google Cloud Datastore vs. JanusGraph vs. Sqrrl

System Properties Comparison Google Cloud Bigtable vs. Google Cloud Datastore vs. JanusGraph vs. Sqrrl

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Adaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value store
Wide column store
Document storeGraph DBMSDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.47
Rank#76  Overall
#12  Document stores
Score1.94
Rank#129  Overall
#12  Graph DBMS
Websitecloud.google.com/­bigtablecloud.google.com/­datastorejanusgraph.orgsqrrl.com
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docsdocs.janusgraph.org
DeveloperGoogleGoogleLinux Foundation; originally developed as Titan by AureliusAmazon infooriginally Sqrrl Data, Inc.
Initial release2015200820172012
Current release0.6.3, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemshostedhostedLinux
OS X
Unix
Windows
Linux
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyes, details hereyesyes
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)nono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Python
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnousing Google App Engineyesno
TriggersnoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication using Paxosyesselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowyes infovia Faunus, a graph analytics engineyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)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.Eventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)User authentification and security via Rexster Graph ServerCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Google Cloud BigtableGoogle Cloud DatastoreJanusGraph infosuccessor of TitanSqrrl
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