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DBMS > Amazon Aurora vs. Bangdb vs. Drizzle vs. Google Cloud Bigtable

System Properties Comparison Amazon Aurora vs. Bangdb vs. Drizzle vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonBangdb  Xexclude from comparisonDrizzle  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.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonConverged and high performance database for device data, events, time series, document and graphMySQL 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.
Primary database modelRelational DBMSDocument store
Graph DBMS
Time Series DBMS
Relational DBMSKey-value store
Wide column store
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websiteaws.amazon.com/­rds/­aurorabangdb.comcloud.google.com/­bigtable
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.bangdb.comcloud.google.com/­bigtable/­docs
DeveloperAmazonSachin Sinha, BangDBDrizzle project, originally started by Brian AkerGoogle
Initial release2015201220082015
Current releaseBangDB 2.0, October 20217.2.4, September 2012
License infoCommercial or Open SourcecommercialOpen Source infoBSD 3Open Source infoGNU GPLcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++
Server operating systemshostedLinuxFreeBSD
Linux
OS X
hosted
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesno
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.yesnono
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialyesno
SQL infoSupport of SQLyesSQL like support with command line toolyes infowith proprietary extensionsno
APIs and other access methodsADO.NET
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
JDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
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#
C++
Java
Python
C
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnonono
Triggersyesyes, Notifications (with Streaming only)no infohooks for callbacks inside the server can be used.no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable consistency, set CAP knob accordinglyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, run db with in-memory only modeno
User concepts infoAccess controlfine grained access rights according to SQL-standardyes (enterprise version only)Pluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon AuroraBangdbDrizzleGoogle Cloud Bigtable
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