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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. Hazelcast vs. Manticore Search

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. Hazelcast vs. Manticore Search

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHazelcast  Xexclude from comparisonManticore Search  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 widely adopted in-memory data gridMulti-storage database for search, including full-text search.
Primary database modelDocument storeTime Series DBMSKey-value storeSearch engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12Time Series DBMS infousing the Manticore Columnar Library
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
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.29
Rank#302  Overall
#21  Search engines
Websitecloud.google.com/­datastorewww.hawkular.orghazelcast.commanticoresearch.com
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidehazelcast.org/­imdg/­docsmanual.manticoresearch.com
DeveloperGoogleCommunity supported by Red HatHazelcastManticore Software
Initial release2008201420082017
Current release5.3.6, November 20236.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen 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 languageJavaJavaC++
Server operating systemshostedLinux
OS X
Windows
All OS with a Java VMFreeBSD
Linux
macOS
Windows
Data schemeschema-freeschema-freeschema-freeFixed schema
Typing infopredefined data types such as float or dateyes, details hereyesyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean
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.nonoyes infothe object must implement a serialization strategyCan index from XML
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query languageSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJCache
JPA
Memcached protocol
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresusing Google App Enginenoyes infoEvent Listeners, Executor Servicesuser defined functions
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on Cassandrayes infoReplicated MapSynchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyesno
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
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
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 Transactionsnoone or two-phase-commit; repeatable reads; read commitedyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.
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)noRole-based access controlno

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More resources
Google Cloud DatastoreHawkular MetricsHazelcastManticore Search
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