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Cassandra

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Vertica

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Cassandra vs Vertica: What are the differences?

Developers describe Cassandra as "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. On the other hand, Vertica is detailed as "Engineering experiences that amaze". Vertica provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.

Cassandra and Vertica belong to "Databases" category of the tech stack.

Cassandra is an open source tool with 5.34K GitHub stars and 2.36K GitHub forks. Here's a link to Cassandra's open source repository on GitHub.

Uber Technologies, Facebook, and Netflix are some of the popular companies that use Cassandra, whereas Vertica is used by Taboola, HomeUnion, and Points International. Cassandra has a broader approval, being mentioned in 431 company stacks & 1388 developers stacks; compared to Vertica, which is listed in 3 company stacks and 3 developer stacks.

Advice on Cassandra and Vertica
Vinay Mehta
Needs advice
on
ScyllaDBScyllaDB
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)
Pankaj Soni
Chief Technical Officer at Software Joint · | 2 upvotes · 77.3K 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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Recommends
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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Recommends
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
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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Pros of Cassandra
Pros of Vertica
  • 115
    Distributed
  • 95
    High performance
  • 80
    High availability
  • 74
    Easy scalability
  • 52
    Replication
  • 26
    Multi datacenter deployments
  • 26
    Reliable
  • 9
    OLTP
  • 7
    Open source
  • 7
    Schema optional
  • 2
    Workload separation (via MDC)
  • 1
    Fast
  • 1
    Shared nothing or shared everything architecture
  • 1
    Offers users the freedom to choose deployment mode
  • 1
    Flexible architecture suits nearly any project
  • 1
    End-to-End ML Workflow Support
  • 1
    All You Need for IoT, Clickstream or Geospatial
  • 1
    Freedom from Underlying Storage
  • 1
    Pre-Aggregation for Cubes (LAPS)
  • 1
    Automatic Data Marts (Flatten Tables)
  • 1
    Near-Real-Time Analytics in pure Column Store
  • 1
    Fully automated Database Designer tool
  • 1
    Query-Optimized Storage
  • 1
    Vertica is the only product which offers partition prun
  • 1
    Partition pruning and predicate push down on Parquet

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Cons of Cassandra
Cons of Vertica
  • 3
    Reliability of replication
  • 1
    Updates
    Be the first to leave a con

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    - No public GitHub repository available -

    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 Vertica?

    It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use Cassandra?
    What companies use Vertica?
    See which teams inside your own company are using Cassandra or Vertica.
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    Sign up to get full access to all the companiesMake informed product decisions

    What tools integrate with Cassandra?
    What tools integrate with Vertica?

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    What are some alternatives to Cassandra and Vertica?
    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.
    Google Cloud Bigtable
    Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.
    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), 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.
    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.
    See all alternatives