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DBMS > Apache Doris vs. Drizzle vs. EsgynDB vs. Google Cloud Datastore vs. Vitess

System Properties Comparison Apache Doris vs. Drizzle vs. EsgynDB vs. Google Cloud Datastore vs. Vitess

Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonDrizzle  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonVitess  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.
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
www.esgyn.cncloud.google.com/­datastorevitess.io
Technical documentationgithub.com/­apache/­doris/­wikicloud.google.com/­datastore/­docsvitess.io/­docs
DeveloperApache Software Foundation, originally contributed from BaiduDrizzle project, originally started by Brian AkerEsgynGoogleThe Linux Foundation, PlanetScale
Initial release20172008201520082013
Current release1.2.2, February 20237.2.4, September 201215.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialcommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++, JavaGo
Server operating systemsLinuxFreeBSD
Linux
OS X
LinuxhostedDocker
Linux
macOS
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes, 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 indexesyesyesyesyesyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsyesSQL-like query language (GQL)yes infowith proprietary extensions
APIs and other access methodsJDBC
MySQL client
JDBCADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesJavaC
C++
Java
PHP
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsnoJava Stored Proceduresusing Google App Engineyes infoproprietary syntax
Triggersnono infohooks for callbacks inside the server can be used.noCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesyesyes infovia ReferenceProperties or Ancestor pathsyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
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.nononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept infono user groups or roles

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More resources
Apache DorisDrizzleEsgynDBGoogle Cloud DatastoreVitess
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