DBMS > BigchainDB vs. Dgraph vs. RRDtool vs. ScyllaDB vs. Snowflake

System Properties Comparison BigchainDB vs. Dgraph vs. RRDtool vs. ScyllaDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Distributed and scalable native Graph DBMS

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Cassandra and DynamoDB compatible wide column store

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Key-value store

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.bigchaindb.com

dgraph.io

oss.oetiker.ch/rrdtool

www.scylladb.com

www.snowflake.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

dgraph.io/docs

oss.oetiker.ch/rrdtool/doc

docs.scylladb.com

docs.snowflake.net/manuals/index.html

Developer

Dgraph Labs, Inc.

Tobias Oetiker

ScyllaDB

Snowflake Computing Inc.

Initial release

2016

1999

2015

2014

Current release

1.8.0, 2022

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

GPL V2 and FLOSS

Open Source

Open Source (AGPL), commercial license available

commercial

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.

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Implementation language

Python

Implementations in Java (e.g. RRD4J) and C# available

C++

Server operating systems

Linux

Linux
OS X
Windows

HP-UX
Linux

Linux

hosted

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

yes

Secondary indexes

yes

cluster global secondary indices

SQL

Support of SQL

SQL-like DML and DDL statements (CQL)

yes

APIs and other access methods

CLI Client
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

in-process shared library
Pipes

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

CLI Client
JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes, Lua

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Synchronous replication via Raft

none

selectable replication factor

Representation of geographical distribution of servers is possible

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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.

yes

in-memory tables

User concepts

Access control

yes

Planned for future releases

Access rights for users can be defined per object

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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