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Azure Cosmos DB

534
986
+ 1
130
Cassandra

3.4K
3.4K
+ 1
504
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Azure Cosmos DB vs Cassandra: What are the differences?

Developers describe Azure Cosmos DB as "A fully-managed, globally distributed NoSQL database service". Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development. On the other hand, Cassandra is detailed 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.

Azure Cosmos DB can be classified as a tool in the "NoSQL Database as a Service" category, while Cassandra is grouped under "Databases".

"Best-of-breed NoSQL features" is the top reason why over 13 developers like Azure Cosmos DB, while over 96 developers mention "Distributed" as the leading cause for choosing Cassandra.

Cassandra is an open source tool with 5.23K GitHub stars and 2.33K GitHub forks. Here's a link to Cassandra's open source repository on GitHub.

According to the StackShare community, Cassandra has a broader approval, being mentioned in 337 company stacks & 230 developers stacks; compared to Azure Cosmos DB, which is listed in 24 company stacks and 23 developer stacks.

Advice on Azure Cosmos DB and Cassandra
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)
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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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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Pankaj Soni
Chief Technical Officer at Software Joint · | 2 upvotes · 115.2K 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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Pros of Azure Cosmos DB
Pros of Cassandra
  • 28
    Best-of-breed NoSQL features
  • 22
    High scalability
  • 15
    Globally distributed
  • 14
    Automatic indexing over flexible json data model
  • 10
    Tunable consistency
  • 10
    Always on with 99.99% availability sla
  • 7
    Javascript language integrated transactions and queries
  • 6
    Predictable performance
  • 5
    High performance
  • 5
    Analytics Store
  • 2
    Rapid Development
  • 2
    No Sql
  • 2
    Auto Indexing
  • 2
    Ease of use
  • 118
    Distributed
  • 97
    High performance
  • 81
    High availability
  • 74
    Easy scalability
  • 52
    Replication
  • 26
    Reliable
  • 26
    Multi datacenter deployments
  • 10
    Schema optional
  • 9
    OLTP
  • 8
    Open source
  • 2
    Workload separation (via MDC)
  • 1
    Fast

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Cons of Azure Cosmos DB
Cons of Cassandra
  • 17
    Pricing
  • 4
    Poor No SQL query support
  • 3
    Reliability of replication
  • 1
    Size
  • 1
    Updates

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- No public GitHub repository available -

What is Azure Cosmos DB?

Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.

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.

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Jobs that mention Azure Cosmos DB and Cassandra as a desired skillset
CBRE
United States of America Texas Richardson
CBRE
United States of America Texas Richardson
CBRE
United States of America Texas Richardson
CBRE
United States of America Texas Richardson
CBRE
United States of America Texas Richardson
LaunchDarkly
London, England, United Kingdom
What companies use Azure Cosmos DB?
What companies use Cassandra?
See which teams inside your own company are using Azure Cosmos DB or Cassandra.
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What tools integrate with Azure Cosmos DB?
What tools integrate with Cassandra?

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What are some alternatives to Azure Cosmos DB and Cassandra?
Azure SQL Database
It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.
MongoDB Atlas
MongoDB Atlas is a global cloud database service built and run by the team behind MongoDB. Enjoy the flexibility and scalability of a document database, with the ease and automation of a fully managed service on your preferred cloud.
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.
Neo4j
Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.
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