It was packaged with the vendor product we bought. Also, it’s good for high performance transactional systems. I'm part of our NoSQL team and Cassandra quickly became a favorite for developers with agile teams.
DynamoDB is good and is also a truly global database as a service on AWS. However, if your organization is not using AWS, then Cassandra will provide a highly scalable and tuneable, consistent database. Cassandra is also fault-tolerant and good for replication across multiple …
Cassandra has its own use case. It performs very well as a data store. Data can be written to it at a high rate. It cannot be compared to traditional RDBMS like Oracle, because they all have their own usage. Even MongoDB, which is somewhat similar, cannot be stacked up against …
We evaluated MongoDB also, but don't like the single point failure possibility. The HBase coupled us too tightly to the Hadoop world while we prefer more technical flexibility. Also HBase is designed for "cold"/old historical data lake use cases and is not typically used for …
Technology selection should be done based on the need and not based on buzz words in the market (google searching). If your data need flat file approach and more searchable based on index and partition keys, then it's better to go for Cassandra. Cassandra is a better choice …
Cassandra is the only NoSQL database I have extensive experience with. In terms of other open source database solutions, I can say that I like Cassandra as much or equally as traditional Oracle MySql, and a lot more than PostgresSQL. The decision to use Cassandra was driven by …
Against HBASE, writes were faster. Reads not so much. Also ability to store in other formats would be good (such as objects). Compared to aerospike, does not compare. Aerospike blows it out of water.
Cassandra does one thing very well. It's able to collect any type of metrics and analytics and store them at very fast speeds. But when it comes to reading the data, there are minor performance issues. That's when other databases such as couchdb or couchbase come in. They can …
Apache Cassandra has the best of both worlds, it is a Java based NoSQL, linearly scalable, best in class
tunable performance across different workloads, fault tolerant, distributed, masterless, time series database. We have used both Apache HBase and MongoDB for some use cases …
Four years ago, I needed to choose a web-scale database. Having used relational databases for years (PostgreSQL is my favorite), I needed something that could perform well at scale with no downtime. I considered VoltDB for its in-memory speed, but it's limited in scale. I …
We also evaluated mySQL and mongoDB. Both of them have their strengths and weaknesses but they are less suited for storing massive amounts of time series data. In addition, they are not elastic by nature and we required a "future-proof" solution as it was difficult to estimate …
Cassandra excels in a broad range of applications -- especially if you understand its data model and write your applications accordingly. It's an excellent choice for time-series data, and a poor choice for application queues. It performs the best if you can simply record history and compute from it, rather than going back and editing or deleting things a lot.
Oracle NoSQL Database is well-suited for you if your data formats are not consistent, if you have limited hardware resources, if you higher data throughput (whether the database is on the cloud or running locally), and if you don't need a declarative query language to maintain a standardized schema of your data. If you need reduced data redundancy and require ACID compliance, you are better off finding an SQL database solution.
High Availability - we utilize the data replication features of Cassandra. This enables us to access our data even when several nodes have gone down
Data Locality - our architecture combines Cassandra storage nodes and computation nodes in the same machine. This enables us to utilize data locality and limit expensive network IO to read data.
Elasticity - Cassandra is a shared nothing architecture. Nodes can be added very easily and they discover the network topology. As soon as a node has joined the Cassandra ring, the data is redistributed among the existing nodes and streamed to it automatically.
Data-model flexibility. Unlike RDBMS solutions, Oracle NoSQL does not restrict you to a predefined set of data types.
Ability to Handle an Increased Amount of Traffic. As Oracle NoSQL can process queries much quicker than Oracle Database, Oracle NoSQL is able to respond to a lot more queries in the same amount of time.
Data-model simplicity. In SQL-oriented databases, there is a learning curve in learning the relationship between databases, tables, rows, and keys. On the other hand, Oracle NoSQL's key-value based storage is much easier to get the hang of.
No Ad-Hoc Queries: Cassandra data storage layer is basically a key-value storage system. This means that you must "model" your data around the queries you want to surface, rather than around the structure of the data itself.
There are no aggregations queries available in Cassandra.
Fewer analytical functions to choose from. When compared to Oracle Database, there is significant difference in the amount of built-in analytical functions.
Eventual data consistency. It is not guaranteed that a write or delete query will be immediately visible for subsequent queries.
Data redundancy. As there are no mechanisms that insure data integrity, users are more likely to have redundant data across their documents.
I would recommend Cassandra DB to those who know their use case very well, as well as know how they are going to store and retrieve data. If you need a guarantee in data storage and retrieval, and a DB that can be linearly grown by adding nodes across availability zones and regions, then this is the database you should choose.
Apache Cassandra has the best of both worlds, it is a Java based NoSQL, linearly scalable, best in class tunable performance across different workloads, fault tolerant, distributed, masterless, time series database. We have used both Apache HBase and MongoDB for some use cases which were within hadoop setup and JSON (JavaScript Object Notation) document store respectively, but given the overall factors favoring Apache Cassandra, it is a technology choice for multiple platforms!
The open source version of Cassandra is only suggested for learning the basic concepts and play with its core features. Unless you really want to invest a lot in your developers and architects knowing every detail of Cassandra, I prefer the DataStax enterprise version. Although the license cost is relatively high, I think they it is worth it. I'm thinking about the support, the monitoring tool OpsCenter, and the integration of Solr and Spark (for data analysis).
Cassandra didn't fully replace our old and traditional relation database Oracle. In addition, it opens another door for us to deal with some special business use cases that NoSQL database can do better in a more feasible and efficient way.
We pay less for computing resources, as Oracle NoSQL databases respond quicker than our previous SQL databases.
Our database administrators and software developers do not need to worry about "data massaging" and can focus on perfecting application logic.
Oracle NoSQL has built-in integration to other Oracle products, so we didn't not need to spend money on building custom integrators or higher additional developers.