Software Alternatives, Accelerators & Startups
Register | Login

Apache Cassandra VS Datrium

Compare Apache Cassandra VS Datrium and see what are their differences

Fileport
The fastest way to send files over the internet featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Apache Cassandra logo Apache Cassandra

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.

Datrium logo Datrium

Get primary storage and backup, disaster recovery orchestration, encryption, and mobility in a single powerful platform. Liberate IT from complexity.
  • Apache Cassandra Landing page
    Landing page //
    2022-04-17
  • Datrium Landing page
    Landing page //
    2021-10-17

Apache Cassandra features and specs

  • Scalability
    Apache Cassandra is designed for linear scalability and can handle large volumes of data across many commodity servers without a single point of failure.
  • High Availability
    Cassandra ensures high availability by replicating data across multiple nodes. Even if some nodes fail, the system remains operational.
  • Performance
    It provides fast writes and reads by using a peer-to-peer architecture, making it highly suitable for applications requiring quick data access.
  • Flexible Data Model
    Cassandra supports a flexible schema, allowing users to add new columns to a table at any time, making it adaptable for various use cases.
  • Geographical Distribution
    Data can be distributed across multiple data centers, ensuring low-latency access for geographically distributed users.
  • No Single Point of Failure
    Its decentralized nature ensures there is no single point of failure, which enhances resilience and fault-tolerance.

Possible disadvantages of Apache Cassandra

  • Complexity
    Managing and configuring Cassandra can be complex, requiring specialized knowledge and skills for optimal performance.
  • Eventual Consistency
    Cassandra follows an eventual consistency model, meaning that there might be a delay before all nodes have the latest data, which may not be suitable for all use cases.
  • Write-heavy Operations
    Although Cassandra handles writes efficiently, write-heavy workloads can lead to compaction issues and increased read latency.
  • Limited Query Capabilities
    Cassandra's query capabilities are relatively limited compared to traditional RDBMS, lacking support for complex joins and aggregations.
  • Maintenance Overhead
    Regular maintenance tasks such as node repair and compaction are necessary to ensure optimal performance, adding to the administrative overhead.
  • Tooling and Ecosystem
    While the ecosystem for Cassandra is growing, it is still not as extensive or mature as those for some other database technologies.

Datrium features and specs

  • Unified Hybrid Cloud Platform
    Datrium provides a comprehensive platform that integrates primary storage, backup, disaster recovery, encryption, and data mobility across on-premises and cloud environments, simplifying management and reducing costs.
  • Scalability
    Datrium's platform is designed to easily scale out for both capacity and performance, allowing organizations to expand their infrastructure as needed without significant overhauls.
  • Simplified Management
    Combining different data management functions into a single platform reduces the complexity of managing multiple systems and provides a streamlined approach for IT teams.
  • Fast Recovery
    With built-in backup and disaster recovery capabilities, Datrium enables near-instantaneous recovery times, ensuring minimal downtime for businesses.
  • Efficient Data Deduplication
    Datrium offers global deduplication and compression across its platform, saving significant storage space and lowering costs by reducing redundancy.

Possible disadvantages of Datrium

  • Initial Integration Complexity
    Organizations might face challenges during the initial implementation phase, particularly in integrating Datrium with existing systems and processes.
  • Cost Considerations
    While Datrium can reduce costs over time, the upfront cost of implementation and licensing may be a barrier for some organizations, especially smaller enterprises.
  • Vendor Lock-in Risk
    Relying on an all-in-one system like Datrium may create dependencies that can be challenging if the organization chooses to switch providers in the future.
  • Learning Curve
    Familiarizing IT staff with Datrium's unique integrated platform may require training and adjustment time, which could be a drawback for fast-paced environments.

Apache Cassandra videos

+ Add

Course Intro | DS101: Introduction to Apache Cassandra™

More videos:

  • Review - Introduction to Apache Cassandra™

Datrium videos

+ Add

Datrium DVX Architecture

More videos:

  • Review - Datrium DVX Data Node Unboxing
  • Review - Introduction to Datrium with Brian Biles

Category Popularity

0-100% (relative to Apache Cassandra and Datrium)

Apache Cassandra

Datrium

Databases
100 100%
Databases
0% 0
Cloud Storage
0 0%
Cloud Storage
100% 100
NoSQL Databases
100 100%
NoSQL Databases
0% 0
Cloud Computing
0 0%
Cloud Computing
100% 100

User comments

Share your experience with using Apache Cassandra and Datrium. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Cassandra and Datrium

Apache Cassandra Reviews

16 Top Big Data Analytics Tools You Should Know About
Application Areas: If you want to work with SQL-like data types on a No-SQL database, Cassandra is a good choice. It is a popular pick in the IoT, fraud detection applications, recommendation engines, product catalogs and playlists, and messaging applications, providing fast real-time insights.
Source: www.analytixlabs.co.in
9 Best MongoDB alternatives in 2019
The Apache Cassandra is an ideal choice for you if you want scalability and high availability without affecting its performance. This MongoDB alternative tool offers support for replicating across multiple datacenters.
Source: www.guru99.com

Datrium Reviews

We have no reviews of Datrium yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Apache Cassandra seems to be more popular. It has been mentiond 44 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Cassandra mentions (44)

  • Why You Shouldn’t Invest In Vector Databases?
    In fact, even in the absence of these commercial databases, users can effortlessly install PostgreSQL and leverage its built-in pgvector functionality for vector search. PostgreSQL stands as the benchmark in the realm of open-source databases, offering comprehensive support across various domains of database management. It excels in transaction processing (e.g., CockroachDB), online analytics (e.g., DuckDB),... - Source: dev.to / about 1 month ago
  • Data integrity in Ably Pub/Sub
    All messages are persisted durably for two minutes, but Pub/Sub channels can be configured to persist messages for longer periods of time using the persisted messages feature. Persisted messages are additionally written to Cassandra. Multiple copies of the message are stored in a quorum of globally-distributed Cassandra nodes. - Source: dev.to / 6 months ago
  • Which Database is Perfect for You? A Comprehensive Guide to MySQL, PostgreSQL, NoSQL, and More
    Cassandra is a highly scalable, distributed NoSQL database designed to handle large amounts of data across many commodity servers without a single point of failure. - Source: dev.to / 11 months ago
  • Consistent Hashing: An Overview and Implementation in Golang
    Distributed storage Distributed storage systems like Cassandra, DynamoDB, and Voldemort also use consistent hashing. In these systems, data is partitioned across many servers. Consistent hashing is used to map data to the servers that store the data. When new servers are added or removed, consistent hashing minimizes the amount of data that needs to be remapped to different servers. - Source: dev.to / about 1 year ago
  • Understanding SQL vs. NoSQL Databases: A Beginner's Guide
    On the other hand, NoSQL databases are non-relational databases. They store data in flexible, JSON-like documents, key-value pairs, or wide-column stores. Examples include MongoDB, Couchbase, and Cassandra. - Source: dev.to / about 1 year ago
View more

Datrium mentions (0)

We have not tracked any mentions of Datrium yet. Tracking of Datrium recommendations started around Mar 2021.

What are some alternatives?

When comparing Apache Cassandra and Datrium, you can also consider the following products

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Zadara Storage - Enterprise Storage-as-a-Service Solutions (STaaS). On premises or in the cloud. Fully-managed 24/7. Pay only for what you use. Leading companies worldwide trust Zadara Data Storage. Proud to be the best cloud storage option

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Azure Storage Explorer - Easily manage your Azure storage accounts in the cloud, from Windows, macOS, or Linux, using Azure Storage Explorer.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

AWS Storage Gateway - AWS Storage Gateway is a service connecting an on-premises software appliance with cloud-based storage.

Loading...