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DBMS > Google Cloud Datastore vs. Greenplum vs. Hypertable vs. KeyDB

System Properties Comparison Google Cloud Datastore vs. Greenplum vs. Hypertable vs. KeyDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGreenplum  Xexclude from comparisonHypertable  Xexclude from comparisonKeyDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.An open source BigTable implementation based on distributed file systems such as HadoopAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelDocument storeRelational DBMSWide column storeKey-value store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score0.70
Rank#229  Overall
#32  Key-value stores
Websitecloud.google.com/­datastoregreenplum.orggithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationcloud.google.com/­datastore/­docsdocs.greenplum.orgdocs.keydb.dev
DeveloperGooglePivotal Software Inc.Hypertable Inc.EQ Alpha Technology Ltd.
Initial release2008200520092019
Current release7.0.0, September 20230.9.8.11, March 2016
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGNU version 3. Commercial license availableOpen Source infoBSD-3
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 languageC++C++
Server operating systemshostedLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linux
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereyesnopartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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.noyes infosince Version 4.2no
Secondary indexesyesyesrestricted infoonly exact value or prefix value scansyes infoby using the Redis Search module
SQL infoSupport of SQLSQL-like query language (GQL)yesnono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
C++ API
Thrift
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Java
Perl
Python
R
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresusing Google App EngineyesnoLua
TriggersCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationselectable replication factor on file system levelMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesyesno
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 ConsistencyImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardnosimple password-based access control and ACL

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More resources
Google Cloud DatastoreGreenplumHypertableKeyDB
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