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DBMS > Dolt vs. etcd vs. eXtremeDB vs. Google Cloud Bigtable vs. Microsoft Azure Cosmos DB

System Properties Comparison Dolt vs. etcd vs. eXtremeDB vs. Google Cloud Bigtable vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines
NameDolt  Xexclude from comparisonetcd  Xexclude from comparisoneXtremeDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparison
DescriptionA MySQL compatible DBMS with Git-like versioning of data and schemaA distributed reliable key-value storeNatively in-memory DBMS with options for persistency, high-availability and clusteringGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Globally distributed, horizontally scalable, multi-model database service
Primary database modelRelational DBMSKey-value storeRelational DBMS
Time Series DBMS
Key-value store
Wide column store
Document store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.96
Rank#193  Overall
#90  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Websitegithub.com/­dolthub/­dolt
www.dolthub.com
etcd.io
github.com/­etcd-io/­etcd
www.mcobject.comcloud.google.com/­bigtableazure.microsoft.com/­services/­cosmos-db
Technical documentationdocs.dolthub.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.mcobject.com/­docs/­extremedb.htmcloud.google.com/­bigtable/­docslearn.microsoft.com/­azure/­cosmos-db
DeveloperDoltHub IncMcObjectGoogleMicrosoft
Initial release2018200120152014
Current release3.4, August 20198.2, 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoGoC and C++
Server operating systemsLinux
macOS
Windows
FreeBSD
Linux
Windows infoexperimental
AIX
HP-UX
Linux
macOS
Solaris
Windows
hostedhosted
Data schemeyesschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesnoyes infoJSON types
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 infosupport of XML interfaces availableno
Secondary indexesyesnoyesnoyes infoAll properties auto-indexed by default
SQL infoSupport of SQLyesnoyes infowith the option: eXtremeSQLnoSQL-like query language
APIs and other access methodsCLI Client
HTTP REST
gRPC
JSON over HTTP
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C
C#
C++
Java
Lua
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Server-side scripts infoStored proceduresyes infocurrently in alpha releasenoyesnoJavaScript
Triggersyesyes, watching key changesyes infoby defining eventsnoJavaScript
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning / shardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Active Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Internal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyeswith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDAtomic single-row operationsMulti-item ACID transactions with snapshot isolation within a partition
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlOnly one user is configurable, and must be specified in the config file at startupnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights can be defined down to the item level
More information provided by the system vendor
DoltetcdeXtremeDBGoogle Cloud BigtableMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» 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
DoltetcdeXtremeDBGoogle Cloud BigtableMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB
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