DBMS > BigchainDB vs. Databend vs. Google BigQuery vs. OpenTSDB

System Properties Comparison BigchainDB vs. Databend vs. Google BigQuery vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Large scale data warehouse service with append-only tables

Scalable Time Series DBMS based on HBase

Primary database model

Document store

Relational DBMS

Time Series DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

www.bigchaindb.com

github.com/datafuselabs/databend
www.databend.com

cloud.google.com/bigquery

opentsdb.net

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.databend.com

cloud.google.com/bigquery/docs

opentsdb.net/docs/build/html/index.html

Developer

Databend Labs

Google

currently maintained by Yahoo and other contributors

Initial release

2016

2021

2010

2011

Current release

1.0.59, April 2023

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache Version 2.0

commercial

Open Source

LGPL

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

Python

Rust

Java

Server operating systems

Linux

hosted
Linux
macOS

hosted

Linux
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
RESTful HTTP API

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP/JSON API

HTTP API
Telnet API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

yes

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

User concepts

Access control

yes

Users with fine-grained authorization concept, user roles

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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