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DBMS > Drizzle vs. Fauna vs. Google Cloud Bigtable vs. HarperDB vs. Microsoft Azure Table Storage

System Properties Comparison Drizzle vs. Fauna vs. Google Cloud Bigtable vs. HarperDB vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonMicrosoft Azure Table Storage  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Fauna 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.HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Key-value store
Wide column store
Document storeWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#143  Overall
#26  Document stores
#13  Graph DBMS
#66  Relational DBMS
#13  Time Series DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.55
Rank#243  Overall
#38  Document stores
Score3.55
Rank#80  Overall
#6  Wide column stores
Websitefauna.comcloud.google.com/­bigtablewww.harperdb.ioazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.fauna.comcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docs
DeveloperDrizzle project, originally started by Brian AkerFauna, Inc.GoogleHarperDBMicrosoft
Initial release20082014201520172012
Current release7.2.4, September 20123.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercial infofree community edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ScalaNode.js
Server operating systemsFreeBSD
Linux
OS X
hostedhostedLinux
OS X
hosted
Data schemeyesschema-freeschema-freedynamic schemaschema-free
Typing infopredefined data types such as float or dateyesnonoyes infoJSON data 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 indexesyesyesnoyesno
SQL infoSupport of SQLyes infowith proprietary extensionsnonoSQL-like data manipulation statementsno
APIs and other access methodsJDBCRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsnoCustom Functions infosince release 3.1no
Triggersno infohooks for callbacks inside the server can be used.nononono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoconsistent hashingShardingA table resides as a whole on one (or more) nodes in a clusterSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definedyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsAtomic execution of specific operationsoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPIdentity management, authentication, and access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesAccess rights based on private key authentication or shared access signatures

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More resources
DrizzleFauna infopreviously named FaunaDBGoogle Cloud BigtableHarperDBMicrosoft Azure Table Storage
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