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Cassandra vs Google Cloud Datastore: What are the differences?
What is Cassandra? A partitioned row store. Rows are organized into tables with a required primary key. Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
What is Google Cloud Datastore? A Fully Managed NoSQL Data Storage Service. Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.
Cassandra can be classified as a tool in the "Databases" category, while Google Cloud Datastore is grouped under "NoSQL Database as a Service".
"Distributed" is the top reason why over 96 developers like Cassandra, while over 4 developers mention "High scalability" as the leading cause for choosing Google Cloud Datastore.
Cassandra is an open source tool with 5.27K GitHub stars and 2.35K GitHub forks. Here's a link to Cassandra's open source repository on GitHub.
According to the StackShare community, Cassandra has a broader approval, being mentioned in 342 company stacks & 240 developers stacks; compared to Google Cloud Datastore, which is listed in 46 company stacks and 16 developer stacks.
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
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 Google Cloud Datastore
- High scalability7
- Serverless2
- Ability to query any property2
- Pay for what you use1
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Cons of Cassandra
- Reliability of replication3
- Size1
- Updates1