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DBMS > Amazon DocumentDB vs. Google Cloud Bigtable vs. HarperDB vs. Hawkular Metrics

System Properties Comparison Amazon DocumentDB vs. Google Cloud Bigtable vs. HarperDB vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonHawkular Metrics  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.HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelDocument storeKey-value store
Wide column store
Document storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.55
Rank#243  Overall
#38  Document stores
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­bigtablewww.harperdb.iowww.hawkular.org
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­bigtable/­docsdocs.harperdb.io/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperGoogleHarperDBCommunity supported by Red Hat
Initial release2019201520172014
Current release3.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree community edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageNode.jsJava
Server operating systemshostedhostedLinux
OS X
Linux
OS X
Windows
Data schemeschema-freeschema-freedynamic schemaschema-free
Typing infopredefined data types such as float or dateyesnoyes infoJSON data typesyes
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 indexesyesnoyesno
SQL infoSupport of SQLnonoSQL-like data manipulation statementsno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP REST
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresnonoCustom Functions infosince release 3.1no
Triggersnononoyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesnoneShardingA table resides as a whole on one (or more) nodes in a clusterSharding infobased on Cassandra
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 zonesyes infothe nodes on which a table resides can be definedselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesnono
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 ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsAtomic single-row operationsAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
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 rights for users and rolesno

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More resources
Amazon DocumentDBGoogle Cloud BigtableHarperDBHawkular Metrics
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