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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelDocument storeTime Series DBMSGraph DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score0.70
Rank#229  Overall
#32  Key-value stores
Websitecloud.google.com/­datastorewww.hawkular.orgjanusgraph.orggithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.janusgraph.orgdocs.keydb.dev
DeveloperGoogleCommunity supported by Red HatLinux Foundation; originally developed as Titan by AureliusEQ Alpha Technology Ltd.
Initial release2008201420172019
Current release0.6.3, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoBSD-3
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Unix
Windows
Linux
Data schemeschema-freeschema-freeyesschema-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 indexesyesnoyesyes infoby using the Redis Search module
SQL infoSupport of SQLSQL-like query language (GQL)nonono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
Clojure
Java
Python
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 EnginenoyesLua
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrayes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on CassandrayesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyes infovia Faunus, a graph analytics engineno
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.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Eventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes 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)noUser authentification and security via Rexster Graph Serversimple password-based access control and ACL

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More resources
Google Cloud DatastoreHawkular MetricsJanusGraph infosuccessor of TitanKeyDB
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