DBMS > GridDB vs. Lovefield vs. ReductStore vs. SwayDB

System Properties Comparison GridDB vs. Lovefield vs. ReductStore vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Key-value store
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	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

griddb.net

google.github.io/lovefield

github.com/reductstore
www.reduct.store

swaydb.simer.au

Technical documentation

docs.griddb.net

github.com/google/lovefield/blob/master/docs/spec_index.md

www.reduct.store/docs

Developer

Toshiba Corporation

Google

ReductStore LLC

Simer Plaha

Initial release

2013

2014

2023

2018

Current release

5.1, August 2022

2.1.12, February 2017

1.9, March 2024

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

Apache 2.0

Open Source

Business Source License 1.1

Open Source

GNU Affero GPL V3.0

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++

JavaScript

C++, Rust

Scala

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP API

Supported programming languages

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

JavaScript

C++
JavaScript (Node.js)
Python
Rust

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Access rights for users can be defined per database

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

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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

Recent citations in the news

General Availability of GridDB® 5.5 Enterprise Edition ~Enhancing the efficiency of IoT system development and ...
16 January 2024, global.toshiba

Toshiba launches cloudy managed IoT database service running its own GridDB
8 April 2021, The Register

GridDB Use case Large-scale high-speed processing of smart meter data following the deregulation of electrical power ...
1 November 2020, global.toshiba

General Availability of GridDB 5.1 Enterprise Edition ~ Continuous database usage in the event of data center failure ...
19 August 2022, global.toshiba

Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ...
3 December 2019, global.toshiba

provided by Google News

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