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DBMS > Amazon DocumentDB vs. Drizzle vs. etcd vs. Fauna vs. Google Cloud Bigtable

System Properties Comparison Amazon DocumentDB vs. Drizzle vs. etcd vs. Fauna vs. Google Cloud Bigtable

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDrizzle  Xexclude from comparisonetcd  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A distributed reliable key-value storeFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelDocument storeRelational DBMSKey-value storeDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score7.25
Rank#54  Overall
#5  Key-value stores
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websiteaws.amazon.com/­documentdbetcd.io
github.com/­etcd-io/­etcd
fauna.comcloud.google.com/­bigtable
Technical documentationaws.amazon.com/­documentdb/­resourcesetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.fauna.comcloud.google.com/­bigtable/­docs
DeveloperDrizzle project, originally started by Brian AkerFauna, Inc.Google
Initial release2019200820142015
Current release7.2.4, September 20123.4, August 2019
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoScala
Server operating systemshostedFreeBSD
Linux
OS X
FreeBSD
Linux
Windows infoexperimental
hostedhosted
Data schemeschema-freeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnonono
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 indexesyesyesnoyesno
SQL infoSupport of SQLnoyes infowith proprietary extensionsnonono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCgRPC
JSON over HTTP
RESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C++
Java
PHP
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononouser defined functionsno
Triggersnono infohooks for callbacks inside the server can be used.yes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication
Source-replica replication
Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnoACIDAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonono
User concepts infoAccess controlAccess rights for users and rolesPluggable authentication mechanisms infoe.g. LDAP, HTTPnoIdentity management, authentication, and access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon DocumentDBDrizzleetcdFauna infopreviously named FaunaDBGoogle Cloud Bigtable
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