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DBMS > Google Cloud Datastore vs. Google Cloud Spanner vs. Hawkular Metrics vs. KeyDB

System Properties Comparison Google Cloud Datastore vs. Google Cloud Spanner vs. Hawkular Metrics vs. KeyDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelDocument storeRelational DBMSTime Series DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Websitecloud.google.com/­datastorecloud.google.com/­spannerwww.hawkular.orggithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationcloud.google.com/­datastore/­docscloud.google.com/­spanner/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.keydb.dev
DeveloperGoogleGoogleCommunity supported by Red HatEQ Alpha Technology Ltd.
Initial release2008201720142019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoBSD-3
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 languageJavaC++
Server operating systemshostedhostedLinux
OS X
Windows
Linux
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyespartial 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.nononono
Secondary indexesyesyesnoyes infoby using the Redis Search module
SQL infoSupport of SQLSQL-like query language (GQL)yes infoQuery statements complying to ANSI 2011nono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP RESTProprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
Go
Java
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 EnginenonoLua
TriggersCallbacks using the Google Apps Enginenoyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication with 3 replicas for regional instances.selectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infousing Google Cloud Dataflownono
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
Strong eventual consistency with CRDTs
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoStrict serializable isolationnoOptimistic 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.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nosimple password-based access control and ACL

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More resources
Google Cloud DatastoreGoogle Cloud SpannerHawkular MetricsKeyDB
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