DBMS > BigchainDB vs. ClickHouse vs. Quasardb vs. Sqrrl vs. TigerGraph

System Properties Comparison BigchainDB vs. ClickHouse vs. Quasardb vs. Sqrrl vs. TigerGraph

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

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

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Distributed, high-performance timeseries database

Adaptable, secure NoSQL built on Apache Accumulo

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

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	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

sqrrl.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

clickhouse.com/docs

doc.quasar.ai/master

docs.tigergraph.com

Developer

Clickhouse Inc.

quasardb

Amazon

originally Sqrrl Data, Inc.

Initial release

2016

2009

2012

2017

Current release

v24.4.1.2088-stable, May 2024

3.14.1, January 2024

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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.

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Implementation language

Python

C++

Java

C++

Server operating systems

Linux

FreeBSD
Linux
macOS

BSD
Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

CLI Client
RESTful HTTP API

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

HTTP API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

Sharding

consistent hashing

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Source-replica replication with selectable replication factor

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

yes

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Cryptographically strong user authentication and audit trail

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

Role-based access control

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