DBMS > Amazon Aurora vs. KairosDB vs. ScyllaDB vs. Snowflake vs. TerminusDB

System Properties Comparison Amazon Aurora vs. KairosDB vs. ScyllaDB vs. Snowflake vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Distributed Time Series DBMS based on Cassandra or H2

Cassandra and DynamoDB compatible wide column store

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Document store

Key-value store

Document store
RDF store

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

aws.amazon.com/rds/aurora

github.com/kairosdb/kairosdb

www.scylladb.com

www.snowflake.com

terminusdb.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

kairosdb.github.io

docs.scylladb.com

docs.snowflake.net/manuals/index.html

terminusdb.github.io/terminusdb/#

Developer

Amazon

ScyllaDB

Snowflake Computing Inc.

DataChemist Ltd.

Initial release

2015

2013

2015

2014

2018

Current release

1.2.2, November 2018

ScyllaDB Open Source 5.4.1, January 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Open Source (AGPL), commercial license available

commercial

Open Source

GPL V3

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

Java

C++

Prolog, Rust

Server operating systems

hosted

Linux
OS X
Windows

Linux

hosted

Linux

Data scheme

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

cluster global secondary indices

SQL

Support of SQL

yes

SQL-like DML and DDL statements (CQL)

yes

SQL-like query language (WOQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

Proprietary protocol (CQL)

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

CLI Client
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
JavaScript

Node.js
PHP
Python

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

JavaScript
Python

Server-side scripts

Stored procedures

yes

yes, Lua

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

Sharding

yes

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

selectable replication factor

Representation of geographical distribution of servers is possible

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Durability

Support for making data persistent

yes

in-memory journaling

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

fine grained access rights according to SQL-standard

simple password-based access control

Access rights for users can be defined per object

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

Role-based access control

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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