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Cassandra vs MonetDB: What are the differences?
## Introduction:
When choosing a database management system, it's crucial to understand the key differences between options like Cassandra and MonetDB. Here are the main differentiators between the two.
1. **Data Model**: Cassandra is a NoSQL database that uses a column-family data model, allowing for flexible schemas and horizontal scalability. On the other hand, MonetDB is a relational database that utilizes a traditional table-based data model with predefined schemas.
2. **Query Language**: Cassandra uses Cassandra Query Language (CQL) which is similar to SQL but has its own syntax and limitations due to its distributed architecture. MonetDB, being a relational database, uses standard SQL for querying, making it easier for users familiar with SQL to work with the database.
3. **Storage Format**: In Cassandra, data is stored in a wide-column format, optimized for write-heavy workloads and horizontal scaling. MonetDB, on the other hand, stores data in columnar format, offering better performance for analytical queries and aggregation operations.
4. **Consistency Model**: Cassandra employs eventual consistency by default, meaning that updates may not be immediately reflected across all nodes in the cluster. MonetDB, being an ACID-compliant relational database, ensures strong consistency by default, making it suitable for use cases where data integrity is a priority.
5. **Performance**: Cassandra is designed for high availability and fault-tolerance, making it suitable for applications requiring constant uptime and high availability. MonetDB, being optimized for analytical workloads, offers superior performance for complex queries and data analysis tasks.
6. **Use Cases**: Cassandra is often used for real-time applications, IoT, and big data analytics due to its scalability and fault-tolerance. MonetDB, on the other hand, is well-suited for OLAP (Online Analytical Processing) applications, data warehousing, and business intelligence tasks where complex queries and data aggregation are common.
In Summary, understanding the key differences between Cassandra and MonetDB in terms of data model, query language, storage format, consistency model, performance, and use cases can help in making an informed decision based on specific requirements and 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
i love syclla for pet projects however it's license which is based on server model is an issue. thus i recommend cassandra
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.
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 MonetDB
- High Performance2
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Cons of Cassandra
- Reliability of replication3
- Size1
- Updates1
Cons of MonetDB
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