FirebirdSQL vs. ScyllaDB

It is able to handle simultaneous connections when using the embedded software version. It is well suited for organizations looking for standalone servers that can handle high data volumes and still perform well and which is also cost-effective database management system especially when they are working on a low budget.

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Scylla is well suited for high-throughput scenarios where keyed data must be read or written with consistently low latency. It's less appropriate for use cases requiring relational queries, secondary indexes, or more structured data sets.

• Performance is really fast.
• It is portable and easy to take back ups.
• Its open n source and free.

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• Low-latency reads
• CQL has a familiar syntax
• Parity with Cassandra
• Practical features

• Documentation.
• No GUI tool to view data.
• Slow via remote access.

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• Better documentation for best practices (e.g., how to effectively use connection pooling)

Because it is free and usually zero maintenance. Just the issue of more difficult format updates in the future lower the rating a bit.

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Usability has improved by unifying the architecture. The only thing's missing out of the box is a simple GUI DB tool for viewing DB contents and maybe running some SQL queries.

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Very easy-to-understand syntax--uses CQL (same as Cassandra), which has many similarities to standard SQL. There are some gotchas, however, that must be known during schema development.

This is an open source project. It provides a fair amount of free documentation and I think forums somewhere...

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The Scylla cloud support team is incredibly responsive and proactive.

Even somebody just starting to use RDBMS himself should get it working quickly, at least if he's got a GUI tool and some SQL knowledge.

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Because it is having Open Source License and easy to deploy on windows and linux environment

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Scylla has a quick learning curve (same as Cassandra) compared to other proprietary solutions like BigTable. It supports higher throughput and lower latency that other NoSQL databases like MongoDB, which sacrifice those features for more flexibility and unique features.

• Cost effective saving us from paid relational database.
• Community support.
• Efficiency in handling simultaneous connections.

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• Addresses latency requirements of our platform