DBMS > Memcached vs. ScyllaDB vs. Snowflake vs. SQream DB vs. Teradata Aster

System Properties Comparison Memcached vs. ScyllaDB vs. Snowflake vs. SQream DB vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

In-memory key-value store, originally intended for caching

Cassandra and DynamoDB compatible wide column store

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

a GPU-based, columnar RDBMS for big data analytics workloads

Platform for big data analytics on multistructured data sources and types

Primary database model

Key-value store

Wide column store

Relational DBMS

Secondary database models

Key-value store

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

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

Technical documentation

github.com/memcached/memcached/wiki

docs.scylladb.com

docs.snowflake.net/manuals/index.html

docs.sqream.com

Developer

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

ScyllaDB

Snowflake Computing Inc.

SQream Technologies

Teradata

Initial release

2003

2015

2014

2017

2005

Current release

1.6.27, May 2024

ScyllaDB Open Source 5.4.1, January 2024

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

BSD license

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

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

FreeBSD
Linux
OS X
Unix
Windows

Linux

hosted

Linux

Data scheme

schema-free

yes

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

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

in Aster File Store

Secondary indexes

yes

cluster global secondary indices

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL)

yes

APIs and other access methods

Proprietary protocol

Proprietary protocol (CQL)

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

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
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

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes, Lua

user defined functions

user defined functions in Python

R packages

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

horizontal and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

selectable replication factor

Representation of geographical distribution of servers is possible

yes

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

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 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

using SASL (Simple Authentication and Security Layer) protocol

Access rights for users can be defined per object

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

fine grained access rights according to SQL-standard

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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