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DBMS > Google BigQuery vs. GridDB vs. Redis

System Properties Comparison Google BigQuery vs. GridDB vs. Redis

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonGridDB  Xexclude from comparisonRedis  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesScalable in-memory time series database optimized for IoT and Big DataIn-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.
Primary database modelRelational DBMSTime Series DBMSKey-value store infoMultiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence
Secondary database modelsKey-value store
Relational DBMS
Document 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
Score33.32
Rank#24  Overall
#15  Relational DBMS
Score0.75
Rank#192  Overall
#10  Time Series DBMS
Score151.86
Rank#7  Overall
#1  Key-value stores
Websitecloud.google.com/­bigquerygriddb.netredis.io
Technical documentationcloud.google.com/­bigquery/­docsdocs.griddb.netredis.io/­documentation
DeveloperGoogleToshiba CorporationSalvatore Sanfilippo infoDevelopment sponsored by Redis Labs
Initial release201020132009
Current release4.5, June 20206.0.8, September 2020
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoBSD 3-Clause, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ScaleGrid for Redis: Fully managed hosting for Redis on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.
Implementation languageC++C
Server operating systemshostedLinuxBSD
Linux
OS X
Windows infoported and maintained by Microsoft Open Technologies, Inc.
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestamppartial 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.nonono
Secondary indexesnoyesyes infowith RediSearch module
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsRESTful HTTP/JSON APIProprietary protocolproprietary protocol infoRESP - REdis Serialization Protocol
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
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 proceduresuser defined functions infoin JavaScriptnoLua
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication infowith Redis Enterprise Pack
Source-replica replication infoChained replication is supported
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACID at container levelOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyes 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.noyesyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) for whole datasets, not for individual tables infoGoogle Cloud Identity & Access Management (IAM)Access rights for users can be defined per databaseSimple password-based access control infoAccess control lists and SSL are available in the commercial version
More information provided by the system vendor
Google BigQueryGridDBRedis
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Google BigQueryGridDBRedis
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