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DBMS > Google Cloud Bigtable vs. Redis vs. TimesTen

System Properties Comparison Google Cloud Bigtable vs. Redis vs. TimesTen

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonRedis  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.In-memory data structure store, used as database, cache and message broker infoRedis focuses on performance so most of its design decisions prioritize high performance and very low latencies.In-Memory RDBMS compatible to Oracle
Primary database modelWide column storeKey-value store infoMultiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistenceRelational DBMS
Secondary database modelsDocument store infowith Redis Modules
Graph DBMS infowith Redis Modules
Search engine infowith Redis Modules
Time Series DBMS infowith Redis Modules
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.06
Rank#82  Overall
#7  Wide column stores
Score155.42
Rank#7  Overall
#1  Key-value stores
Score2.35
Rank#116  Overall
#56  Relational DBMS
Websitecloud.google.com/­bigtableredis.iowww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationcloud.google.com/­bigtable/­docsredis.io/­documentationdocs.oracle.com/­database/­timesten-18.1
DeveloperGoogleSalvatore Sanfilippo infoDevelopment sponsored by Redis LabsOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release201520091998
Current release6.0.9, October 202011 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialOpen Source infoBSD 3-Clause, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC
Server operating systemshostedBSD
Linux
OS X
Windows infoported and maintained by Microsoft Open Technologies, Inc.
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenopartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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.nonono
Secondary indexesnoyes infowith RediSearch moduleyes
SQL infoSupport of SQLnonoyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
proprietary protocol infoRESP - REdis Serialization ProtocolJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
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
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnoLuaPL/SQL
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication infowith Redis Enterprise Pack
Source-replica replication infoChained replication is supported
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsOptimistic locking, atomic execution of commands blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoData access is serialized by the serveryes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes 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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Simple password-based access control infoAccess control lists and SSL are available in the commercial versionfine grained access rights according to SQL-standard
More information provided by the system vendor
Google Cloud BigtableRedisTimesTen
Specific characteristicsThe world's first commercial In-Memory Relational Database offering (launched in...
» more
Competitive advantagesTimesTen offers many advantages over competing products: Mature product with nearly...
» more
Typical application scenariosTimesTen can be used in a wide range of application areas. Some examples include:...
» more
Key customersSome of our key customers include Ericsson , Telcordia , China Mobile, China Telecom,...
» more
Market metricsTimesTen is used by thousands of customers in tens of thousands of deployments worldwide...
» more
Licensing and pricing modelsStandard Oracle licence models ; end user and ISV/OEM licence terms available.
» more

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Related products and services
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
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Datadog: Monitor all Redis metrics: hit rates, clients, commands per second, and more.
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More resources
Google Cloud BigtableRedisTimesTen
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Recent citations in the news

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud Bigtable Replication Out of Beta After Just One Month
14 May 2019, Computer Business Review

Google Expands Cloud BigTable Replication Capabilities Globally in Beta
20 March 2019, InfoQ.com

Google Launches Cloud Bigtable, A Highly Scalable And Performant NoSQL Database
6 May 2015, TechCrunch

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