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DBMS > Amazon DocumentDB vs. Google Cloud Bigtable vs. HBase vs. WakandaDB

System Properties Comparison Amazon DocumentDB vs. Google Cloud Bigtable vs. HBase vs. WakandaDB

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHBase  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Wide-column store based on Apache Hadoop and on concepts of BigTableWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument storeKey-value store
Wide column store
Wide column storeObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­bigtablehbase.apache.orgwakanda.github.io
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­bigtable/­docshbase.apache.org/­book.htmlwakanda.github.io/­doc
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetWakanda SAS
Initial release2019201520082012
Current release2.3.4, January 20212.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaScript
Server operating systemshostedhostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesnooptions to bring your own types, AVROyes
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 indexesyesnono
SQL infoSupport of SQLnononono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
Thrift
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
JavaScript
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javayes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesyesno
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 Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsAtomic single-row operationsSingle row ACID (across millions of columns)ACID
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.noyesno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes

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More resources
Amazon DocumentDBGoogle Cloud BigtableHBaseWakandaDB
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