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Cassandra vs Memcached: What are the differences?
Key Differences between Cassandra and Memcached
Cassandra and Memcached are both popular distributed database systems, but they have several key differences.
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Data Model:
- Cassandra: Cassandra is a wide column store database, which means that it organizes data into rows and columns similar to a traditional relational database.
- Memcached: Memcached is a key-value store database, where data is stored and retrieved based on unique keys.
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Data Persistence:
- Cassandra: Cassandra supports data persistence, which means that data is stored permanently on disk even after a system failure or shutdown.
- Memcached: Memcached does not provide data persistence. Data is stored in-memory only and is lost upon system failure or shutdown.
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Scalability:
- Cassandra: Cassandra is designed to scale horizontally, meaning that it can handle large volumes of data and high traffic loads by adding more machines to the cluster.
- Memcached: Memcached is primarily designed to scale vertically, meaning that it can handle higher traffic loads by adding more resources (CPU, RAM) to a single machine.
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Data Distribution:
- Cassandra: Cassandra uses a peer-to-peer distributed architecture and employs a distributed hash table to evenly distribute data across multiple nodes in a cluster.
- Memcached: Memcached uses a client-server architecture, where data is distributed based on a hash function across multiple server instances.
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Consistency Model:
- Cassandra: Cassandra offers tunable consistency levels, allowing the user to choose between strong consistency and eventual consistency based on their specific needs.
- Memcached: Memcached does not provide consistency guarantees. It focuses on providing high-speed data retrieval and caching.
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Query Language:
- Cassandra: Cassandra uses its own query language called CQL (Cassandra Query Language), which is similar to SQL and provides a powerful set of features for data manipulation and retrieval.
- Memcached: Memcached does not have a query language. Data can only be accessed by specifying the key associated with the desired value.
In summary, Cassandra is a wide column store database with support for data persistence, horizontal scalability, and offers tunable consistency levels, while Memcached is a key-value store database without data persistence, focuses on vertical scalability, and does not provide consistency guarantees.
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.
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.
i love syclla for pet projects however it's license which is based on server model is an issue. thus i recommend cassandra
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.
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 Memcached
- Fast object cache139
- High-performance129
- Stable91
- Mature65
- Distributed caching system33
- Improved response time and throughput11
- Great for caching HTML3
- Putta2
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Cons of Cassandra
- Reliability of replication3
- Size1
- Updates1
Cons of Memcached
- Only caches simple types2
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