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Cassandra

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Cassandra vs Scylla: What are the differences?

Cassandra: A partitioned row store. Rows are organized into tables with a required primary key. 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; Scylla: Next Generation Cassandra. Real-time big data database, with scale-up performance of 1,000,000 IOPS per node, scale-out to 100s of nodes and 99 latency of less than 1 msec.

Cassandra and Scylla can be categorized as "Databases" tools.

Cassandra and Scylla are both open source tools. Cassandra with 5.27K GitHub stars and 2.35K forks on GitHub appears to be more popular than Scylla with 5.18K GitHub stars and 615 GitHub forks.

Uber Technologies, Facebook, and Spotify are some of the popular companies that use Cassandra, whereas Scylla is used by Investing.com, Dstillery, and Yieldbot. Cassandra has a broader approval, being mentioned in 342 company stacks & 240 developers stacks; compared to Scylla, which is listed in 11 company stacks and 5 developer stacks.

Advice on Cassandra and Scylla
Vinay Mehta
Needs advice
on
ScyllaScylla
and
CassandraCassandra

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
ScyllaScylla

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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Pankaj Soni
Chief Technical Officer at Software Joint · | 2 upvotes · 61.9K views
Recommends
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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Alex Peake
Recommends
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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Recommends
ScyllaScylla

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 Cassandra and Scylla
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 Cassandra
Pros of Scylla
  • 114
    Distributed
  • 95
    High performance
  • 80
    High availability
  • 74
    Easy scalability
  • 52
    Replication
  • 26
    Multi datacenter deployments
  • 26
    Reliable
  • 8
    OLTP
  • 7
    Open source
  • 7
    Schema optional
  • 2
    Workload separation (via MDC)
  • 1
    Fast
  • 1
    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 Cassandra
Cons of Scylla
  • 2
    Reliability of replication
  • 1
    Updates
    Be the first to leave a con

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    What is 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.

    What is Scylla?

    Real-time big data database, with scale-up performance of 1,000,000 IOPS per node, scale-out to 100s of nodes and 99 latency of less than 1 msec.

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    What tools integrate with Cassandra?
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    What are some alternatives to Cassandra and Scylla?
    HBase
    Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
    Hadoop
    The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
    Redis
    Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
    Couchbase
    Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
    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.
    See all alternatives