DBMS > GridDB vs. Oracle NoSQL vs. PostGIS vs. Sadas Engine vs. Transwarp Hippo

System Properties Comparison GridDB vs. Oracle NoSQL vs. PostGIS vs. Sadas Engine vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

Description

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Spatial extension of PostgreSQL

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Time Series DBMS

Document store
Key-value store
Relational DBMS

Spatial DBMS

Relational DBMS

Vector DBMS

Secondary database models

Key-value store
Relational DBMS

Relational DBMS

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

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

griddb.net

www.oracle.com/database/nosql/technologies/nosql

postgis.net

www.sadasengine.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.griddb.net

docs.oracle.com/en/database/other-databases/nosql-database/index.html

postgis.net/documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Toshiba Corporation

Oracle

SADAS s.r.l.

Initial release

2013

2011

2005

2006

2023

Current release

5.1, August 2022

23.3, December 2023

3.4.2, February 2024

8.0

1.0, May 2023

License

Commercial or Open Source

Open Source

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

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

GPL v2.0

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C++

Server operating systems

Linux

Linux
Solaris SPARC/x86

AIX
Linux
Windows

Linux
macOS

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

optional

yes

Vector, Numeric and String

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

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

Supported programming languages

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

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++
Java
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

based on PostgreSQL

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

configurable

ACID within a storage node (=shard)

ACID

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

off heap cache

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

Access rights for users can be defined per database

Access rights for users and roles

yes

based on PostgreSQL

Access rights for users, groups and roles according to SQL-standard

Role based access control and fine grained access rights

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

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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