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Redis

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Redis vs Scylla: What are the differences?

  1. Key Difference 1: Data Structure: Redis is a key-value store that offers various data structures such as strings, lists, sets, sorted sets, etc., making it highly flexible for different use cases. On the other hand, Scylla is a highly scalable NoSQL database that is built upon Apache Cassandra and focuses on providing wide column store functionality. It organizes data into tables with a defined schema, allowing for efficient querying and storage of large datasets.
  2. Key Difference 2: Data Distribution: Redis utilizes a master-slave replication model, where multiple slave nodes can replicate data from a single master node. This provides high availability and read scalability but limits write scalability. In contrast, Scylla follows a masterless distributed architecture using consistent hashing and gossip protocols. It allows for automatic partitioning and distribution of data across multiple nodes, ensuring high write and read scalability.
  3. Key Difference 3: Durability: Redis offers durability through a combination of techniques such as point-in-time snapshots, append-only files, and asynchronous replication. However, it is optimized for in-memory operations and may not be as suitable for scenarios with large datasets or high write frequencies. Scylla, on the other hand, is designed for durability, supporting both in-memory and on-disk storage. It integrates with distributed file systems and provides configurable levels of data persistence to meet various durability requirements.
  4. Key Difference 4: Consistency Models: Redis supports multiple consistency models, including eventual consistency and strong consistency, depending on the data structure used. It allows applications to choose the level of consistency required for their use case. Scylla follows a tunable consistency model, giving developers the ability to define their desired consistency level on a per-operation basis. This flexibility allows for a trade-off between consistency, availability, and partition tolerance.
  5. Key Difference 5: Query Language: Redis uses a simple query language that operates directly on its data structures. It supports a set of commands and pipelines, making it easy to manipulate and retrieve data. Scylla, being a wide column store, utilizes the CQL (Cassandra Query Language) which is similar to SQL but adapted for use in NoSQL databases. CQL provides powerful querying capabilities with support for filtering, data aggregation, and secondary indexes.
  6. Key Difference 6: Performance and Scaling: Redis is known for its exceptional performance as an in-memory database. It can handle high volumes of operations with low latencies. However, when it comes to scaling beyond the capacity of a single node, Redis requires additional sharding and partitioning mechanisms. Scylla, being designed for horizontal scalability from the ground up, performs exceptionally well at massive scales. It efficiently utilizes hardware resources across a cluster of nodes, making it ideal for high-performance and high-throughput applications.

In Summary, Redis and Scylla differ in terms of their data structure flexibility, data distribution models, durability options, consistency models, query languages, and performance/scaling capabilities.

Advice on Redis and ScyllaDB
Vinay Mehta
Needs advice
on
CassandraCassandra
and
ScyllaDBScyllaDB

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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Replies (4)
Recommends
on
ScyllaDBScyllaDB

Scylla can handle 1M/s events with a simple data model quite easily. The api to query is CQL, we have REST api but that's for control/monitoring

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Alex Peake
Recommends
on
CassandraCassandra

Cassandra is quite capable of the task, in a highly available way, given appropriate scaling of the system. Remember that updates are only inserts, and that efficient retrieval is only by key (which can be a complex key). Talking of keys, make sure that the keys are well distributed.

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Pankaj Soni
Chief Technical Officer at Software Joint · | 2 upvotes · 160K views
Recommends
on
CassandraCassandra

i love syclla for pet projects however it's license which is based on server model is an issue. thus i recommend cassandra

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Recommends
on
ScyllaDBScyllaDB

By 55M do you mean 55 million entity changes per 2 minutes? It is relatively high, means almost 460k per second. If I had to choose between Scylla or Cassandra, I would opt for Scylla as it is promising better performance for simple operations. However, maybe it would be worth to consider yet another alternative technology. Take into consideration required consistency, reliability and high availability and you may realize that there are more suitable once. Rest API should not be the main driver, because you can always develop the API yourself, if not supported by given technology.

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Decisions about Redis and ScyllaDB
Tom Klein

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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Pros of Redis
Pros of ScyllaDB
  • 886
    Performance
  • 542
    Super fast
  • 513
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
  • 194
    Open source
  • 182
    Easy to deploy
  • 164
    Stable
  • 155
    Free
  • 121
    Fast
  • 42
    High-Performance
  • 40
    High Availability
  • 35
    Data Structures
  • 32
    Very Scalable
  • 24
    Replication
  • 22
    Great community
  • 22
    Pub/Sub
  • 19
    "NoSQL" key-value data store
  • 16
    Hashes
  • 13
    Sets
  • 11
    Sorted Sets
  • 10
    NoSQL
  • 10
    Lists
  • 9
    Async replication
  • 9
    BSD licensed
  • 8
    Bitmaps
  • 8
    Integrates super easy with Sidekiq for Rails background
  • 7
    Keys with a limited time-to-live
  • 7
    Open Source
  • 6
    Lua scripting
  • 6
    Strings
  • 5
    Awesomeness for Free
  • 5
    Hyperloglogs
  • 4
    Transactions
  • 4
    Outstanding performance
  • 4
    Runs server side LUA
  • 4
    LRU eviction of keys
  • 4
    Feature Rich
  • 4
    Written in ANSI C
  • 4
    Networked
  • 3
    Data structure server
  • 3
    Performance & ease of use
  • 2
    Dont save data if no subscribers are found
  • 2
    Automatic failover
  • 2
    Easy to use
  • 2
    Temporarily kept on disk
  • 2
    Scalable
  • 2
    Existing Laravel Integration
  • 2
    Channels concept
  • 2
    Object [key/value] size each 500 MB
  • 2
    Simple
  • 2
    Replication
  • 1
    Fewer nodes
  • 1
    Distributed
  • 1
    Scale up
  • 1
    High availability
  • 1
    Written in C++
  • 1
    High performance

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Cons of Redis
Cons of ScyllaDB
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL
    Be the first to leave a con

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    What is Redis?

    Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

    What is ScyllaDB?

    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.

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    What companies use Redis?
    What companies use ScyllaDB?
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    What tools integrate with Redis?
    What tools integrate with ScyllaDB?

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    What are some alternatives to Redis and ScyllaDB?
    Memcached
    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.
    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.
    RabbitMQ
    RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
    Hazelcast
    With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.
    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.
    See all alternatives