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Cassandra

Cassandra

Overview

What is Cassandra?

Cassandra is a no-SQL database from Apache.

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Learn from top reviewers

review of cassandra

Rating: 6 out of 10
April 7, 2021
IncentivizedVetted ReviewVerified User
Used for specific product (which is used by whole organization). Addressing for column store we need for uniqueness of proprietary information that Redis and Mongo does not su...
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Anson Abraham
Engineer - Engineering
Data Lord
PlaceIQ
Apache Cassandra7 years of experience

One of the Best NoSQL Databases!

Rating: 8 out of 10
June 30, 2019
IncentivizedVetted ReviewVerified User
Cassandra is currently used for our enterprise eCommerce platform. So far our experience is good with Cassandra its an extremely powerful NoSQL Database with high performance—...
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Priti Asai / Thakkar
Engineer - Engineering
Lead Software Engineer
macys.com
Apache Cassandra5 years of experience

Cassandra at scale

Rating: 8 out of 10
March 16, 2019
IncentivizedVetted ReviewVerified User
It’s one of the database platforms we offer to the development community in our organization. We have various selections when it comes to databases including DB2, SQL Server, ...
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Glen Kim
Consultant - Information Technology
Senior Software Engineer
USAA
Apache Cassandra1 year of experience

Cassandra - a tunable NoSQL datastore

Rating: 9 out of 10
March 7, 2019
IncentivizedVetted ReviewVerified User
Cassandra is a NoSQL database which is used to store a large amount of data quickly. It has a very fast write speed, allowing a large volume of data storage within a small amo...
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Dhruba Jyoti Nag
Analyst - Information Technology
Associate
Cognizant
Apache Cassandra2 years of experience

Pretty good software

Rating: 8 out of 10
February 26, 2019
IncentivizedVetted ReviewVerified User
Cassandra is used in my organization by my department to handle data that is not in a standard RDMBS format.
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Feng Cai
Advisor - Information Technology
DB2 UDB DBA
CVS Caremark
Apache Cassandra2 years of experience
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Pricing

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Cassandra

Cassandra

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What is Cassandra?

Cassandra is a no-SQL database from Apache.

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  • No setup fee

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Product Demos

Presto and Cassandra: Doing SQL and Joins on Cassandra Tables

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CassandraDB Connector Demo | CassandraDB Integration

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Open Source BI Tools and Cassandra

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Real-time IoT data analytics and visualization with Kaa, Apache Cassandra, and Apache Zeppelin

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Features

NoSQL Databases

NoSQL databases are designed to be used across large distrusted systems. They are notably much more scalable and much faster and handling very large data loads than traditional relational databases.

8
Avg 8.8
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Product Details

What is Cassandra?

Cassandra Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

Cassandra is a no-SQL database from Apache.

Reviewers rate Scalability highest, with a score of 9.5.

The most common users of Cassandra are from Enterprises (1,001+ employees).
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Reviews From Top Reviewers

View all reviews
(1-5 of 16)

Cassandra Usage and Needs

Rating: 8 out of 10
Incentivized
September 27, 2017
RR
Ravi Reddy
Lead Engineer Consultant
TEKSystems [Client : Target] (Retail, 10,001+ employees)
Vetted Review
Verified User
Apache Cassandra
4 years of experience
View profile
Use Cases and Deployment Scope
We are using Cassandra based on the requirements and data availability to the application (based on queries for search).
Pros
  • Cassandra lot of API's ready available for map reducing queries (like materialized queries).
  • Cassandra uses ring architecture approach, there is no master-slave approach (like HBase). If data is published on the node, the data will get synced with other nodes in the ring architecture, compared to HBase which has a dedicated master node to orchestrate the data into its slaves.
  • Write Speed
  • Multi Data Center Replication
  • Tunable Consistency
  • Integrates with JVM because it's written in Java
  • Cassandra Query Language is a subset of SQL query (less learning curve)
Cons
  • No Ad-Hoc Queries: Cassandra data storage layer is basically a key-value storage system. This means that you must "model" your data around the queries you want to surface, rather than around the structure of the data itself.
  • There are no aggregations queries available in Cassandra.
  • Not fit for transactional data.
Likelihood to Recommend
Cassandra data storage layer is basically a key-value storage system. This means that you must model your data around the queries you want to surface, rather than around the structure of the data itself. This can lead to storing the data multiple times in different ways to be able to satisfy the requirements of your application.

Cassandra, hands-on review, after 4 years of serious use

Rating: 10 out of 10
Incentivized
October 16, 2015
DP
David Prinzing
Chief Technology Officer
Algorithmic Ads (Marketing and Advertising, 1-10 employees)
Vetted Review
Verified User
Apache Cassandra
4 years of experience
Use Cases and Deployment Scope
Cassandra is the only database used by Algorithmic Ads. We use it for both real-time transactions and analytics. The primary application accessing Cassandra is a light-weight Java application that provides a RESTful web services API for all our other applications. The API is a focal point for integration and includes both business logic and data. The same API is used both internally and by our customers. We rely on Cassandra for its amazing performance, linear scalability, and continuous availability.
Pros
  • Continuous availability: as a fully distributed database (no master nodes), we can update nodes with rolling restarts and accommodate minor outages without impacting our customer services.
  • Linear scalability: for every unit of compute that you add, you get an equivalent unit of capacity. The same application can scale from a single developer's laptop to a web-scale service with billions of rows in a table.
  • Amazing performance: if you design your data model correctly, bearing in mind the queries you need to answer, you can get answers in milliseconds.
  • Time-series data: Cassandra excels at recording, processing, and retrieving time-series data. It's a simple matter to version everything and simply record what happens, rather than going back and editing things. Then, you can compute things from the recorded history.
Cons
  • Cassandra is a poor choice for implementing application queues.
  • NoSQL requires thinking differently, and can be challenging for people with strong relational database backgrounds to understand. The CQL language helps with this, but it pays to understand how the engine works under the hood. That said, the benefits outweigh the challenge of the learning curve!
  • Database compactions and anti-entropy repair can be burdensome on a busy cluster. Significant improvements have been made in recent versions, but it remains as an operational challenge.
Likelihood to Recommend
Cassandra excels in a broad range of applications -- especially if you understand its data model and write your applications accordingly. It's an excellent choice for time-series data, and a poor choice for application queues. It performs the best if you can simply record history and compute from it, rather than going back and editing or deleting things a lot.

Cassandra, put into the real business context

Rating: 8 out of 10
Incentivized
October 30, 2017
yS
yixiang Shan
IT Strategic Technical Advisor
FedEx Express (Package/Freight Delivery, 10,001+ employees)
Vetted Review
Verified User
Apache Cassandra
3 years of experience
View profile
Use Cases and Deployment Scope
We use Cassandra to build a fully functional POC (with the continuous production level volume of feeding data) for a shipment cloud concept for Fedex's EMEA region. This solution is composed of two parts, we use an IMDG product to keep the latest transaction of all shipments' latest "status" while we use Cassandra as our long-term transaction storage to keep all historical shipment status update events. On top of those InMemory and NoSQL storage, we built one unified RESTful based service, which depends on the user's query needs, either/and/or query the IMDG for the latest status of the shipment or query the Cassandra for the history of the shipment. Also, the Cassandra is used as the "backup" of the IMDG, in case the IMDG part is fully crashed (the worst scenario). Thanks to the time series way of persisting the data in Cassandra, we still can extract the "latest" status of a shipment from Cassandra's full transaction history with reasonable performance (slower than IMDG but much quicker than the traditional relational database).
Pros
  • Cassandra is very strong for saving the time series based transaction data model, simply by reversing the time series order when creating the data table, we can very quickly fetch the "latest" records even from millions of associated transactions because the latest record is always at the top of the search. By combining with the TTL feature of the Cassandra column, it is easy to "auto" delete the old data.
  • Cassandra combines the key-value store from Amazon's DynamoDB with the column family data model from the Google's BigTable, which makes it easy to manage both structured and non-structured data model efficiently.
  • By using the DataStax Enterprise version provided Solr integration, it can even solve some ad-hoc query needs which may not be fully taken into account at the beginning of the project when the data table is created. This extremely adds more room to play for a large enterprise or project which does require some flexibility in the practical context.
  • The linear scalability provided by Cassandra, allowing us to easily scale up/down the cluster by simply adding/removing the servers.
  • The throughput for both the read/write performance of Cassandra is quite good.
Cons
  • Managing the big cluster of Cassandra , even with the DataStax Enterprise Version, is still quite challenging for a maintenance team, considering the frequent version upgrade (even in the rolling fashion) and more frequent auto-repair, for me on this area, a powerful tool should be provided to "automate" this process as much as possible.
  • The TTL design is good, however the pain is if the TTL is set on some data already inserted, it can not be simply updated. Unless that data is reinserted again, this fact causes a lot of issues in case the business strategy is changed which requires the purge strategy to be updated also.
  • As the nature of Cassandra is still Java based, the GC sometimes eats some performance, if Cassandra can allow using more non-Heap memory space, to reduce the GC efforts which will free more power on the hardware.
  • The default indexing strategy for JSON formatted data in the DataStax's Solr integration is not available. At this moment we have to implement our own to support our JSON text stored. We extract the key field from our data which might be required to be ad-hoc searched, converting them into the JSON format (only one level Map), and save them into the Cassandra column. On top of that we want Solr to index the key of each token.
Likelihood to Recommend
For the scenarios which need ACID support, maybe Cassandra is not the best, but for an insert only (time series based) transaction case and requirements to cope with the unpredictable data model/structure changes of the future, then Cassandra is one of the best options. If you only use the open source version of Cassandra, then without Solr integrated, you need to know your search query before you create the table, if that's not possible then Cassandra or other NoSQL DB might not your right choice.

Cassandra: A highly available and scalable database

Rating: 8 out of 10
Incentivized
March 15, 2019
Verified User
Team Lead in Engineering
Financial Services Company, 10,001+ employees
Vetted Review
Verified User
Apache Cassandra
3 years of experience
Use Cases and Deployment Scope
We use Cassandra as the NoSQL database for our use cases. We stream a lot of API data into this database and rely on the availability it gives us. It has proven to be consistent, which we use to our advantage. Cassandra can distribute data across multiple machines in an app-transparent manner, thus helping us to expand it on demand.
Pros
  • Cassandra is a masterless design, hence massively scalable. It is great for applications and use cases that cannot afford to lose data. There is no single point of failure.
  • You can add more nodes to Cassandra to linearly increase your transactions/requests. Also, it has great support across cloud regions and data centers.
  • Cassandra provides features like tunable consistency, data compression and CQL(Cassandra Query Language) which we use.
Cons
  • The underlying medium of Cassandra is a key-value store. So when you model your data, it is based on how you would want to query it and not how the data is structured. This results in a repetition of data when storing. Hence, there is no referential integrity - there is no concept of JOIN connections in Cassandra.
  • Data aggregation functions like SUM, MIN, MAX, AVG, and others are very costly even if possible. Hence Ad-hoc query or analysis is difficult.
Likelihood to Recommend
You should be very clear where you want to use Cassandra because there is no referential integrity (JOIN) in Cassandra. You have to model data based on how you want to query it, hence what use cases it can be used for should be considered carefully.

You can use it where you want to store log or user-behavior types of data. You can use it in heavy-write or time-series data storage. It is good in retail applications for fast product catalog inputs and lookups

Pretty good software

Rating: 8 out of 10
Incentivized
February 26, 2019
FC
Feng Cai
DB2 UDB DBA
CVS Caremark (Hospital & Health Care, 10,001+ employees)
Vetted Review
Verified User
Apache Cassandra
2 years of experience
View profile
Use Cases and Deployment Scope
Cassandra is used in my organization by my department to handle data that is not in a standard RDMBS format.
Pros
  • Runs on commodity hardware
  • Build in fault tolerance
  • Can grow horizontally
Cons
  • It is a bit difficult for people that come from the SQL world.
  • Managing anti-entropy repair is still a bit of a challenge.
  • Better security patches.
Likelihood to Recommend
Nothing beats software that works and charges nothing. It handles data that is not fit for traditional RDBMS. However, not a lot of employees know how to use it efficiently.
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