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DBMS > Drizzle vs. etcd vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics

System Properties Comparison Drizzle vs. etcd vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  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.A distributed reliable key-value storeAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelRelational DBMSKey-value storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastoreazure.microsoft.com/­services/­synapse-analytics
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsdocs.microsoft.com/­azure/­synapse-analytics
DeveloperDrizzle project, originally started by Brian AkerGoogleMicrosoft
Initial release200820082016
Current release7.2.4, September 20123.4, August 2019
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC++
Server operating systemsFreeBSD
Linux
OS X
FreeBSD
Linux
Windows infoexperimental
hostedhosted
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes, details hereyes
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 indexesyesnoyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoSQL-like query language (GQL)yes
APIs and other access methodsJDBCgRPC
JSON over HTTP
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Supported programming languagesC
C++
Java
PHP
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
PHP
Server-side scripts infoStored proceduresnonousing Google App EngineTransact SQL
Triggersno infohooks for callbacks inside the server can be used.yes, watching key changesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.Immediate Consistency
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes

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More resources
DrizzleetcdGoogle Cloud DatastoreMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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