DBMS > Alibaba Cloud Table Store vs. Badger vs. Firebase Realtime Database vs. GridDB vs. Heroic

System Properties Comparison Alibaba Cloud Table Store vs. Badger vs. Firebase Realtime Database vs. GridDB vs. Heroic

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Secondary database models

Key-value store
Relational DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Website

www.alibabacloud.com/product/table-store

github.com/dgraph-io/badger

firebase.google.com/products/realtime-database

griddb.net

github.com/spotify/heroic

Technical documentation

www.alibabacloud.com/help/en/tablestore

godoc.org/github.com/dgraph-io/badger

firebase.google.com/docs/database

docs.griddb.net

spotify.github.io/heroic

Developer

Alibaba

DGraph Labs

Google

acquired by Google 2014

Toshiba Corporation

Spotify

Initial release

2016

2017

2012

2013

2014

Current release

5.1, August 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

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

Open Source

Apache 2.0

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++

Java

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

hosted

Linux

Data scheme

schema-free

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

via Elasticsearch

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

Java
Python

Java
JavaScript
Objective-C

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Source-replica replication

yes

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

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate consistency within container, eventual consistency across containers

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

yes

ACID at container level

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

User concepts

Access control

Access rights based on subaccounts and tokens

yes, based on authentication and database rules

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

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

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12 December 2019, Paul Andlinger

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