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DBMS > Google Cloud Bigtable vs. Hazelcast vs. OrigoDB vs. TimesTen

System Properties Comparison Google Cloud Bigtable vs. Hazelcast vs. OrigoDB vs. TimesTen

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonOrigoDB  Xexclude from comparisonTimesTen  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 gridA fully ACID in-memory object graph databaseAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelKey-value store
Wide column store
Key-value storeDocument store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score5.72
Rank#59  Overall
#6  Key-value stores
Score0.00
Rank#385  Overall
#54  Document stores
#21  Object oriented DBMS
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websitecloud.google.com/­bigtablehazelcast.comorigodb.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docsorigodb.com/­docsdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperGoogleHazelcastRobert Friberg et alOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release201520082009 infounder the name LiveDB1998
Current release5.3.6, November 2023Release 22.1
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#
Server operating systemshostedAll OS with a Java VMLinux
Windows
IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesUser defined using .NET types and collectionsyes
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 strategyno infocan be achieved using .NETno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like query languagenoyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
HTTP API
LINQ
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.NetC
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor ServicesyesPL/SQL
Triggersnoyes infoEventsyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronizednone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated MapSource-replica replicationMulti-source replication
Source-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 AlgorithmImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonodepending on modelyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsone or two-phase-commit; repeatable reads; read commitedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlRole based authorizationfine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableHazelcastOrigoDBTimesTen
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