Overview

Memcached

Stacks7.9K

Followers5.7K

Votes473

GitHub Stars14.0K

Forks3.3K

ScyllaDB

Stacks143

Followers197

Votes8

Memcached vs Scylla: What are the differences?

# Key Differences between Memcached and Scylla

Memcached and Scylla are both popular choices for caching and data storage in modern applications, but they differ in several key aspects. 

1. **Data Model**: Memcached is a simple key-value store, while Scylla is a distributed NoSQL database that supports a wide range of data models including wide columns, JSON, and more. This difference in data model capabilities gives Scylla more flexibility in handling various types of data compared to Memcached.

2. **Consistency**: Memcached provides eventual consistency, meaning that there can be a delay in data synchronization across nodes. On the other hand, Scylla offers strong consistency with support for tunable consistency levels, ensuring data accuracy and integrity in distributed environments.

3. **Scaling**: Memcached is designed to be a caching layer and may not scale as efficiently for large datasets or high-throughput applications. In contrast, Scylla is built for horizontal scalability, allowing it to handle massive amounts of data and traffic with ease.

4. **Data Persistence**: Memcached is an in-memory store with no built-in persistence, meaning that data can be lost if a node fails. In comparison, Scylla offers durable data storage by persisting data to disk, ensuring data integrity even in the event of hardware failures.

5. **Deployment Complexity**: Setting up and maintaining a Memcached cluster is relatively straightforward, making it easier to deploy for smaller projects or temporary caching needs. On the other hand, deploying Scylla requires more operational overhead due to its distributed nature and configuration options.

6. **Query Language**: Memcached does not provide a query language, as it simply stores and retrieves key-value pairs. In contrast, Scylla supports CQL (Cassandra Query Language), a powerful SQL-like language for interacting with the database, offering more advanced querying capabilities.

In Summary, Memcached and Scylla differ in terms of data model, consistency, scaling capabilities, data persistence, deployment complexity, and query language support.

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Advice on Memcached, ScyllaDB

Tom

CEO at Gentlent

Jun 9, 2020

Decided

The Gentlent Tech Team made lots of updates within the past year. The biggest one being our database:

We decided to migrate our #PostgreSQL -based database systems to a custom implementation of #Cassandra . This allows us to integrate our product data perfectly in a system that just makes sense. High availability and scalability are supported out of the box.

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Vinay

Head of Engineering

Sep 19, 2019

Needs advice

The problem I have is - we need to process & change(update/insert) 55M Data every 2 min and this updated data to be available for Rest API for Filtering / Selection. Response time for Rest API should be less than 1 sec.

The most important factors for me are processing and storing time of 2 min. There need to be 2 views of Data One is for Selection & 2. Changed data.

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Detailed Comparison

Memcached	ScyllaDB
Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.	ScyllaDB is the database for data-intensive apps that require high performance and low latency. It enables teams to harness the ever-increasing computing power of modern infrastructures – eliminating barriers to scale as data grows.
-	High availability; horizontal scalability; vertical scalability; Cassandra compatible; DynamoDB compatible; wide column; NoSQL; lightweight transactions; change data capture; workload prioritization; shard-per-core; IO scheduler; self-tuning
Statistics
GitHub Stars 14.0K	GitHub Stars -
GitHub Forks 3.3K	GitHub Forks -
Stacks 7.9K	Stacks 143
Followers 5.7K	Followers 197
Votes 473	Votes 8
Pros & Cons
Pros 139 Fast object cache 129 High-performance 91 Stable 65 Mature 33 Distributed caching system Cons 2 Only caches simple types	Pros 2 Replication 1 High availability 1 Scale up 1 High performance 1 Distributed
Integrations
No integrations available	KairosDB Wireshark JanusGraph Grafana Hackolade Prometheus Kubernetes Datadog Kafka Apache Spark

What are some alternatives to Memcached, ScyllaDB?

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.