Software Alternatives, Accelerators & Startups

Dashbird VS Apache Cassandra

Compare Dashbird VS Apache Cassandra and see what are their differences

Dashbird logo Dashbird

End-to-end observability & debugging platform for serverless applications.

Apache Cassandra logo Apache Cassandra

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
  • Dashbird Landing page
    Landing page //
    2023-08-27

Dashbird is an observability, debugging, and intelligence platform designed specifically to help serverless developers build, operate, improve, and scale their modern cloud applications on AWS environment fast, securely, and with ease. It’s free to use for up to 1M invocations and doesn’t require any code changes.

Dashbird fills the gaps left by CloudWatch and other traditional monitoring tools by offering enhanced out-of-the-box monitoring, operations, and actionable insights tools for architectural improvements, all in one place.

Full observability covered for AWS services: Lambda, API Gateway, DynamoDB, SQS, ECS, Step Functions, Kinesis, HTTP API Gateway, RDS, SNS, OpenSearch, ELB.

Dashbird’s approach is fairly simple, all the mission-critical data of your entire serverless system is placed in a single dashboard giving you a birds-eye-view of the entire system activity. Moreover, you get immediate alerts on any errors or warnings that may arise and get pointed to the exact point of failure in the system so it can be resolved fast.

The 3 core pillars of Dashbird are:

Real-time end-to-end serverless observability Automatic Failure Detection Continuous Well-Architected reports on your entire infrastructure

  • Apache Cassandra Landing page
    Landing page //
    2022-04-17

Dashbird features and specs

  • Serverless observability: yes
  • Error and warning alerting: yes
  • Well-Architected Reports: yes
  • Quick log search: yes

Apache Cassandra features and specs

No features have been listed yet.

Dashbird videos

Dashbird explained

Apache Cassandra videos

Course Intro | DS101: Introduction to Apache Cassandra™

More videos:

  • Review - Introduction to Apache Cassandra™

Category Popularity

0-100% (relative to Dashbird and Apache Cassandra)
AWS Lambda
100 100%
0% 0
Databases
0 0%
100% 100
Monitoring Tools
100 100%
0% 0
NoSQL Databases
0 0%
100% 100

User comments

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Reviews

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

Dashbird Reviews

We have no reviews of Dashbird yet.
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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.
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

Social recommendations and mentions

Dashbird might be a bit more popular than Apache Cassandra. We know about 59 links to it since March 2021 and only 41 links to Apache Cassandra. 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.

Dashbird mentions (59)

  • Monitor Your AWS AppSync GraphQL APIs with Simplicity
    There's more to come at Dashbird, as we're already building more features to help you run the best possible AppSync endpoints. This includes a set of well-architected insights to guide you with best practices. - Source: dev.to / over 1 year ago
  • An Introduction to Function as a Service (FaaS)
    Observability in serverless Tools like Datadog, Splunk, Thundra.io, New Relic, and Dashbird make monitoring and debugging serverless applications easy. They collect metrics, logs, and traces from AWS Cloudwatch and X-ray. - Source: dev.to / almost 2 years ago
  • Why and how to monitor Amazon API Gateway HTTP APIs
    With its latest release, Dashbird added support for APIG's HTTP APIs. All your HTTP APIs are automatically monitored after installing Dashbird into your AWS account. You need to deploy a CloudFormation template to set up Dashbird integration; it doesn't require any code changes! - Source: dev.to / almost 2 years ago
  • Serverless monitoring — the good, the bad and the ugly
    I decided to try out Dashbird because it’s free and seems promising. They’re not asking for a credit card either, making it a “why not try it out” situation. - Source: dev.to / about 2 years ago
  • We can do better failure detection in serverless applications
    With the emergence of managed and distributed services, the monitoring landscape will have to go through a significant change to keep up with modern cloud applications. Currently, devops overhead is one of the biggest obstacles for companies looking to use serverless in production and rely on it for mission-critical applications. Our team at Dashbird is hoping to solve that one problem at a time. - Source: dev.to / about 2 years ago
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Apache Cassandra mentions (41)

  • 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 / 30 days 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 2 months ago
  • How to choose the right type of database
    HBase and Cassandra: Both cater to non-structured Big Data. Cassandra is geared towards scenarios requiring high availability with eventual consistency, while HBase offers strong consistency and is better suited for read-heavy applications where data consistency is paramount. - Source: dev.to / 3 months ago
  • Asynchronous driver written in Rust for ScyllaDB, Cassandra and AWS Keyspaces.
    Dear r/python, we are happy to present you with our first open-source project. We have managed to implement a new driver for Python that works with Apache Cassandra, ScyllaDB and AWS Keyspaces. Source: 9 months ago
  • How to Choose the Right Document-Oriented NoSQL Database for Your Application
    NoSQL is a term that we have become very familiar with in recent times and it is used to describe a set of databases that don't make use of SQL when writing & composing queries. There are loads of different types of NoSQL databases ranging from key-value databases like the Reddis to document-oriented databases like MongoDB and Firestore to graph databases like Neo4J to multi-paradigm databases like FaunaDB and... - Source: dev.to / 9 months ago
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What are some alternatives?

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

Lumigo - With one-click distributed tracing, Lumigo lets developers effortlessly find and fix issues in serverless and microservices environments.

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

Epsagon - Track costs and fix your serverless application.

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

Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.

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