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DBMS > Amazon Aurora vs. Drizzle vs. Google Cloud Bigtable vs. Manticore Search

System Properties Comparison Amazon Aurora vs. Drizzle vs. Google Cloud Bigtable vs. Manticore Search

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonManticore Search  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 and PostgreSQL compatible cloud service by AmazonMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Multi-storage database for search, including full-text search.
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Search engine
Secondary database modelsDocument storeTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.50
Rank#49  Overall
#31  Relational DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score0.23
Rank#317  Overall
#21  Search engines
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­bigtablemanticoresearch.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­bigtable/­docsmanual.manticoresearch.com
DeveloperAmazonDrizzle project, originally started by Brian AkerGoogleManticore Software
Initial release2015200820152017
Current release7.2.4, September 20126.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLcommercialOpen Source infoGPL version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedFreeBSD
Linux
OS X
hostedFreeBSD
Linux
macOS
Windows
Data schemeyesyesschema-freeFixed schema
Typing infopredefined data types such as float or dateyesyesnoInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean
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.yesnoCan index from XML
Secondary indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLyesyes infowith proprietary extensionsnoSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
JDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresyesnonouser defined functions
Triggersyesno infohooks for callbacks inside the server can be used.nono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesSynchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Amazon AuroraDrizzleGoogle Cloud BigtableManticore Search
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