DBMS > Blueflood vs. chDB vs. GridDB vs. LevelDB vs. Riak KV

System Properties Comparison Blueflood vs. chDB vs. GridDB vs. LevelDB vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

An embedded SQL OLAP Engine powered by ClickHouse

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Time Series DBMS

Key-value store
Relational DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.07
Rank	#376	Overall
	#158	Relational DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

blueflood.io

github.com/chdb-io/chdb

griddb.net

github.com/google/leveldb

Technical documentation

github.com/rax-maas/blueflood/wiki

doc.chdb.io

docs.griddb.net

github.com/google/leveldb/blob/main/doc/index.md

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Rackspace

Toshiba Corporation

Google

OpenSource, formerly Basho Technologies

Initial release

2013

2023

2013

2011

2009

Current release

5.1, August 2022

1.23, February 2021

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

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

Open Source

BSD

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Erlang

Server operating systems

Linux
OS X

server-less

Linux

Illumos
Linux
OS X
Windows

Linux
OS X

Data scheme

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

restricted

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

HTTP REST

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

Supported programming languages

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

none

selectable replication factor

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

ACID at container level

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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 for users can be defined per database

yes, using Riak Security

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.

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