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DBMS > etcd vs. Google Cloud Bigtable vs. GridDB vs. Microsoft Azure Cosmos DB vs. TinkerGraph

System Properties Comparison etcd vs. Google Cloud Bigtable vs. GridDB vs. Microsoft Azure Cosmos DB vs. TinkerGraph

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionA distributed reliable key-value storeGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable in-memory time series database optimized for IoT and Big DataGlobally distributed, horizontally scalable, multi-model database serviceA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelKey-value storeKey-value store
Wide column store
Time Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Graph DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.64
Rank#54  Overall
#5  Key-value stores
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score29.85
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score0.12
Rank#344  Overall
#34  Graph DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­bigtablegriddb.netazure.microsoft.com/­services/­cosmos-dbtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­bigtable/­docsdocs.griddb.netlearn.microsoft.com/­azure/­cosmos-db
DeveloperGoogleToshiba CorporationMicrosoft
Initial release2015201320142009
Current release3.4, August 20195.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++Java
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedLinuxhosted
Data schemeschema-freeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datenonoyes infonumerical, string, blob, geometry, boolean, timestampyes infoJSON typesyes
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 indexesnonoyesyes infoAll properties auto-indexed by defaultno
SQL infoSupport of SQLnonoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageno
APIs and other access methodsgRPC
JSON over HTTP
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
TinkerPop 3
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Groovy
Java
Server-side scripts infoStored proceduresnononoJavaScriptno
Triggersyes, watching key changesnoyesJavaScriptno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Internal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobswith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency within container, eventual consistency across containersBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
none
Foreign keys infoReferential integritynonononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID at container levelMulti-item ACID transactions with snapshot isolation within a partitionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
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 can be defined per databaseAccess rights can be defined down to the item levelno
More information provided by the system vendor
etcdGoogle Cloud BigtableGridDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBTinkerGraph
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
etcdGoogle Cloud BigtableGridDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBTinkerGraph
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