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DBMS > Google Cloud Bigtable vs. GridDB vs. Netezza vs. Qdrant

System Properties Comparison Google Cloud Bigtable vs. GridDB vs. Netezza vs. Qdrant

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonQdrant  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.Scalable in-memory time series database optimized for IoT and Big DataData warehouse and analytics appliance part of IBM PureSystemsA high-performance vector database with neural network or semantic-based matching
Primary database modelKey-value store
Wide column store
Time Series DBMSRelational DBMSVector DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score1.16
Rank#175  Overall
#6  Vector DBMS
Websitecloud.google.com/­bigtablegriddb.netwww.ibm.com/­products/­netezzagithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationcloud.google.com/­bigtable/­docsdocs.griddb.netqdrant.tech/­documentation
DeveloperGoogleToshiba CorporationIBMQdrant
Initial release2015201320002021
Current release5.1, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache Version 2.0
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 languageC++Rust
Server operating systemshostedLinuxLinux infoincluded in applianceDocker
Linux
macOS
Windows
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyes infonumerical, string, blob, geometry, boolean, timestampyesNumbers, Strings, Geo, 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.nonono
Secondary indexesnoyesyesyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yesno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
OLE DB
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnonoyes
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationSource-replica replicationCollection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesno
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 within container, eventual consistency across containersEventual Consistency, tunable consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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)Access rights for users can be defined per databaseUsers with fine-grained authorization conceptKey-based authentication
More information provided by the system vendor
Google Cloud BigtableGridDBNetezza infoAlso called PureData System for Analytics by IBMQdrant
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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More resources
Google Cloud BigtableGridDBNetezza infoAlso called PureData System for Analytics by IBMQdrant
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