DBMS > Google Cloud Datastore vs. GridDB vs. Oracle

System Properties Comparison Google Cloud Datastore vs. GridDB vs. Oracle

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Scalable in-memory time series database optimized for IoT and Big Data

Widely used RDBMS

Primary database model

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Key-value store
Relational DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	3.70
Rank	#71	Overall
	#12	Document stores

Score	2.00
Rank	#114	Overall
	#9	Time Series DBMS

Score	1231.05
Rank	#1	Overall
	#1	Relational DBMS

Website

cloud.google.com/datastore

griddb.net

www.oracle.com/database

Technical documentation

cloud.google.com/datastore/docs

docs.griddb.net

docs.oracle.com/en/database

Developer

Google

Toshiba Corporation

Oracle

Initial release

2008

2013

1980

Current release

5.1, August 2022

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C and C++

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes, details here

yes

numerical, string, blob, geometry, boolean, timestamp

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (GQL)

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

using Google App Engine

PL/SQL

also stored procedures in Java possible

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID at container level

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL is the DBMS of the Year 2019
3 January 2020, Matthias Gelbmann, Paul Andlinger

The struggle for the hegemony in Oracle's database empire
2 May 2017, Paul Andlinger

Architecting eCommerce Platforms for Zero Downtime on Black Friday and Beyond
25 November 2016, Tony Branson (guest author)

show all

Recent citations in the news

Observability: cloud monitoring and logging
18 November 2024, Google Cloud

Best Cloud Storage Options for All Your Data in 2025
16 April 2025, CNET

AWS vs Azure vs Google Cloud in 2025: Cloud Comparison
6 April 2025, Cloudwards.net

(PDF) Implementation Google Cloud Platform as Data Storage in Industry
22 October 2024, ResearchGate

Enabling Security for Hadoop Data Lake on Google Cloud Storage
30 July 2024, Uber

provided by Google News

Toshiba's GridDB® Cloud Database Service for Big Data and IoT is Now Available Globally
17 April 2025, The Korea Herald

Enterprise Edition with Improved Fault Tolerance and a New Affordable Monthly Plan for GridDB
15 October 2024, global.toshiba

Toshiba’s GridDB cloud goes global: Powering the backbone of data-driven transformation - CRN
18 April 2025, India

Toshiba’s GridDB Cloud Database Service for Big Data and IoT is now available globally - CRN
17 April 2025, India

Toshiba launches cloudy managed IoT database service running its own GridDB
8 April 2021, theregister.com

provided by Google News

Oracle and Google Cloud Announce Industry-First Partner Program and Powerful New Capabilities for Oracle Database@Google Cloud
9 April 2025, Oracle

Oracle and Microsoft Add Powerful, Flexible New Services to Oracle Database@Azure and Expand Regional Availability
20 March 2025, Oracle

Oracle and Google Cloud Expand Regional Availability and Add Powerful New Capabilities to Oracle Database@Google Cloud
30 January 2025, Oracle

DXC Technology migrates global SaaS suite to Oracle Autonomous Database on OCI
13 April 2025, Oracle

Oracle Database@AWS Available in Limited Preview
2 December 2024, Oracle

provided by Google News

Share this page