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DBMS > Google Cloud Bigtable vs. Hazelcast vs. Manticore Search vs. OrigoDB

System Properties Comparison Google Cloud Bigtable vs. Hazelcast vs. Manticore Search vs. OrigoDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonManticore Search  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely adopted in-memory data gridMulti-storage database for search, including full-text search.A fully ACID in-memory object graph database
Primary database modelKey-value store
Wide column store
Key-value storeSearch engineDocument store
Object oriented DBMS
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
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.29
Rank#302  Overall
#21  Search engines
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Websitecloud.google.com/­bigtablehazelcast.commanticoresearch.comorigodb.com
Technical documentationcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docsmanual.manticoresearch.comorigodb.com/­docs
DeveloperGoogleHazelcastManticore SoftwareRobert Friberg et al
Initial release2015200820172009 infounder the name LiveDB
Current release5.3.6, November 20236.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2Open Source
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C#
Server operating systemshostedAll OS with a Java VMFreeBSD
Linux
macOS
Windows
Linux
Windows
Data schemeschema-freeschema-freeFixed schemayes
Typing infopredefined data types such as float or datenoyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, BooleanUser defined using .NET types and collections
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 infothe object must implement a serialization strategyCan index from XMLno infocan be achieved using .NET
Secondary indexesnoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query languageSQL-like query languageno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
.NET Client API
HTTP API
LINQ
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesuser defined functionsyes
Triggersnoyes infoEventsnoyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated MapSynchronous replication based on Galera librarySource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynononodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsone or two-phase-commit; repeatable reads; read commitedyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlnoRole based authorization

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More resources
Google Cloud BigtableHazelcastManticore SearchOrigoDB
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