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DBMS > Google Cloud Datastore vs. HarperDB vs. Hawkular Metrics vs. Percona Server for MongoDB

System Properties Comparison Google Cloud Datastore vs. HarperDB vs. Hawkular Metrics vs. Percona Server for MongoDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHarperDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A drop-in replacement for MongoDB Community Edition with enterprise-grade features.
Primary database modelDocument storeDocument storeTime Series DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.60
Rank#244  Overall
#38  Document stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.60
Rank#246  Overall
#39  Document stores
Websitecloud.google.com/­datastorewww.harperdb.iowww.hawkular.orgwww.percona.com/­mongodb/­software/­percona-server-for-mongodb
Technical documentationcloud.google.com/­datastore/­docsdocs.harperdb.io/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.percona.com/­percona-distribution-for-mongodb
DeveloperGoogleHarperDBCommunity supported by Red HatPercona
Initial release2008201720142015
Current release3.1, August 20213.4.10-2.10, November 2017
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache 2.0Open Source infoGPL Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageNode.jsJavaC++
Server operating systemshostedLinux
OS X
Linux
OS X
Windows
Linux
Data schemeschema-freedynamic schemaschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereyes infoJSON data typesyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like data manipulation statementsnono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP RESTproprietary protocol using JSON
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Server-side scripts infoStored proceduresusing Google App EngineCustom Functions infosince release 3.1noJavaScript
TriggersCallbacks using the Google Apps Enginenoyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infothe nodes on which a table resides can be definedselectable replication factor infobased on CassandraSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Immediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic execution of specific operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infovia In-Memory Engine
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesnoAccess rights for users and roles

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More resources
Google Cloud DatastoreHarperDBHawkular MetricsPercona Server for MongoDB
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