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Cassandra vs RethinkDB: What are the differences?
# Introduction
Cassandra and RethinkDB are both popular NoSQL databases known for their scalability, high availability, and fault tolerance. However, there are key differences between the two that make them suitable for different use cases.
1. **Data Model**:
Cassandra follows a wide column data model, allowing flexible schema design and column-based storage. In contrast, RethinkDB employs a JSON document model, providing a more structured and nested data representation.
2. **Query Language**:
Cassandra uses CQL (Cassandra Query Language), which is SQL-like and optimized for data retrieval. RethinkDB utilizes ReQL (RethinkDB Query Language), a functional query language with support for real-time queries via changefeeds.
3. **Consistency Level**:
Cassandra offers tunable consistency levels, allowing users to balance between consistency and availability. RethinkDB maintains strong consistency by default, ensuring that all nodes see the same data at the same time.
4. **Horizontal Scalability**:
Cassandra is designed for linear scalability, making it ideal for large-scale distributed deployments. RethinkDB supports sharding for horizontal scalability, enabling a distributed architecture but may require more management overhead.
5. **Data Durability**:
Cassandra provides durable writes through its commit log and storage engine, ensuring data persistence even in the event of node failures. RethinkDB offers strong durability guarantees by synchronously writing data to disk on multiple nodes for fault tolerance.
6. **Real-time Updates**:
RethinkDB excels in real-time applications with its built-in support for changefeeds, allowing applications to receive updates as soon as they occur. Cassandra lacks native support for real-time updates, requiring additional tools or integration for similar functionality.
In Summary, while both Cassandra and RethinkDB offer scalability and fault tolerance, they differ in data models, query languages, consistency levels, scalability options, durability mechanisms, and real-time update capabilities, making them suitable for distinct use cases.
Developing a solution that collects Telemetry Data from different devices, nearly 1000 devices minimum and maximum 12000. Each device is sending 2 packets in 1 second. This is time-series data, and this data definition and different reports are saved on PostgreSQL. Like Building information, maintenance records, etc. I want to know about the best solution. This data is required for Math and ML to run different algorithms. Also, data is raw without definitions and information stored in PostgreSQL. Initially, I went with TimescaleDB due to PostgreSQL support, but to increase in sites, I started facing many issues with timescale DB in terms of flexibility of storing data.
My major requirement is also the replication of the database for reporting and different purposes. You may also suggest other options other than Druid and Cassandra. But an open source solution is appreciated.
Hi Umair, Did you try MongoDB. We are using MongoDB on a production environment and collecting data from devices like your scenario. We have a MongoDB cluster with three replicas. Data from devices are being written to the master node and real-time dashboard UI is using the secondary nodes for read operations. With this setup write operations are not affected by read operations too.
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.
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
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.
i love syclla for pet projects however it's license which is based on server model is an issue. thus i recommend cassandra
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.
Fauna is a serverless database where you store data as JSON. Also, you have build in a HTTP GraphQL interface with a full authentication & authorization layer. That means you can skip your Backend and call it directly from the Frontend. With the power, that you can write data transformation function within Fauna with her own language called FQL, we're getting a blazing fast application.
Also, Fauna takes care about scaling and backups (All data are sharded on three different locations on the globe). That means we can fully focus on writing business logic and don't have to worry anymore about infrastructure.
I’m newbie I was developing a pouchdb and couchdb app cause if the sync. Lots of learning very little code available. I dropped the project cause it consumed my life. Yeats later I’m back into it. I researched other db and came across rethinkdb and mongo for the subscription features. With socketio I should be able to create and similar sync feature. Attempted to use mongo. I attempted to use rethink. Rethink for the win. Super clear l. I had it running in minutes on my local machine and I believe it’s supposed to scale easy. Mongo wasn’t as easy and there free online db is so slow what’s the point. Very easy to find mongo code examples and use rethink code in its place. I wish I went this route years ago. All that corporate google Amazon crap get bent. The reason they have so much power in the world is cause you guys are giving it to them.
Pros of Cassandra
- Distributed119
- High performance98
- High availability81
- Easy scalability74
- Replication53
- Reliable26
- Multi datacenter deployments26
- Schema optional10
- OLTP9
- Open source8
- Workload separation (via MDC)2
- Fast1
Pros of RethinkDB
- Powerful query language48
- Excellent dashboard46
- JSON42
- Distributed database41
- Open source38
- Reactive25
- Atomic updates16
- Joins15
- MVCC concurrency9
- Hadoop-style map/reduce9
- Geospatial support4
- Real-time, open-source, scalable4
- YC Company2
- A NoSQL DB with joins2
- Great Admin UI2
- Changefeeds: no polling needed to get updates2
- Fast, easily scalable, great customer support2
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Cons of Cassandra
- Reliability of replication3
- Size1
- Updates1
Cons of RethinkDB
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