Apache Cassandra vs. EDB Postgres Advanced Server vs. PostgreSQL

Apache Cassandra is a NoSQL database and well suited where you need highly available, linearly scalable, tunable consistency and high performance across varying workloads. It has worked well for our use cases, and I shared my experiences to use it effectively at the last Cassandra summit! http://bit.ly/1Ok56TK It is a NoSQL database, finally you can tune it to be strongly consistent and successfully use it as such. However those are not usual patterns, as you negotiate on latency. It works well if you require that. If your use case needs strongly consistent environments with semantics of a relational database or if the use case needs a data warehouse, or if you need NoSQL with ACID transactions, Apache Cassandra may not be the optimum choice.

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It's great if you are using or wish to use PostgreSQL and need the added performance optimization, security features and developer and DBA tools. If you need compatibility with Oracle it's a must-have. There are many developer features that greatly assist dev teams in integrating and implementing complex middleware. It's great for optimizing complex database queries as well as for scaling. I would recommend Postgres Plus Advanced Server for any software development team that is hitting the limit of what PostgreSQL is capable of and wants to improve performance, security, and gain extra developer tools.

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PostgreSQL is best used for structured data, and best when following relational database design principles. I would not use PostgreSQL for large unstructured data such as video, images, sound files, xml documents, web-pages, especially if these files have their own highly variable, internal structure.

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• Continuous availability: as a fully distributed database (no master nodes), we can update nodes with rolling restarts and accommodate minor outages without impacting our customer services.
• Linear scalability: for every unit of compute that you add, you get an equivalent unit of capacity. The same application can scale from a single developer's laptop to a web-scale service with billions of rows in a table.
• Amazing performance: if you design your data model correctly, bearing in mind the queries you need to answer, you can get answers in milliseconds.
• Time-series data: Cassandra excels at recording, processing, and retrieving time-series data. It's a simple matter to version everything and simply record what happens, rather than going back and editing things. Then, you can compute things from the recorded history.

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• PPAS Oracle compatibility, especially the PL/SQL syntax, has made migrating database-tier code very simple. Most Oracle packages do not need to be changed at all and those that do are generally for simple reasons like a reserved word in PPAS that is allowed in Oracle.
• PPAS xDB, the multi-master replication tool, is simple and - most important - does not break with network or other interruptions. We have been able to configure and forget, which our customers could never do with other multi-master tools.
• Most people had no idea that PPAS and PostgreSQL have full CRUD support for JSON. They think you need a specialized product and/or that JSON is read-only. Every organization that I have worked with is evaluating adding JSON to their relational model.

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• It works well with external data sources and runs on platforms with stable performance.
• Clients can rest assured that their personal information will be safe and secure.
• Many forums discuss setup and usage, and most are free.
• Adding tooling applications to a computer is unlimited.
• PostgreSQL runs on many OS platforms and supports ANSI SQL, stored procedures, and triggers.

• Cassandra runs on the JVM and therefor may require a lot of GC tuning for read/write intensive applications.
• Requires manual periodic maintenance - for example it is recommended to run a cleanup on a regular basis.
• There are a lot of knobs and buttons to configure the system. For many cases the default configuration will be sufficient, but if its not - you will need significant ramp up on the inner workings of Cassandra in order to effectively tune it.

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• Documentation is excellent but spread out across many resources and can take a while to wade through—would benefit from having more intro level, getting started guides for various languages.
• Ruby support is excellent but more Ruby examples and beginner-level documentation would be nice.
• It is sometimes hard to find a community of users on StackOverflow so a larger community, and a dedicated forum with active members to answer questions and work through issues would be nice.

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• Clearer indications on what is the query plan, to optimize the query
• More out of the box, Postgres specific, SQL functions
• It would be nice to have a more visual aid of the relationship between all tables, but possibly this depend more on the UI used

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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.

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As a needed software for day to day development activities

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It’s great tool but it can be complicated when it comes administration and maintenance.

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Postgresql is the best tool out there for relational data so I have to give it a high rating when it comes to analytics, data availability and consistency, so on and so forth. SQL is also a relatively consistent language so when it comes to building new tables and loading data in from the OLTP database, there are enough tools where we can perform ETL on a scalable basis.

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PostgreSQL's availability is top notch. Apart from connection time-out for an idle user, the database is super reliable.

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The data queries are relatively quick for a small to medium sized table. With complex joins, and a wide and deep table however, the performance of the query has room for improvement.

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Sometimes instead giving straight answer, we ‘re getting transfered to talk professional service.

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There are several companies that you can contract for technical support, like EnterpriseDB or Percona, both first level in expertise and commitment to the software.

But we do not have contracts with them, we have done all the way from googling to forums, and never have a problem that we cannot resolve or pass around. And for dozens of projects and more than 15 years now.

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The online training is request based. Had there been recorded videos available online for potential users to benefit from, I could have rated it higher. The online documentation however is very helpful. The online documentation PDF is downloadable and allows users to pace their own learning. With examples and code snippets, the documentation is great starting point.

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The online documentation of the PostgreSQL product is elaborate and takes users step by step.

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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 web and mobile applications due to its performance concern. Cassandra, by contrast, offers the availability and performance necessary for developing highly available applications. Furthermore, the Hadoop technology stack is typically deployed in a single location, while in the big international enterprise context, we demand the feasibility for deployment across countries and continents, hence finally we are favor of Cassandra

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PPAS proved better for our customer's data-centric apps than Oracle in all but a few edge cases (encryption at rest and multi-TB database-tier backups) because it is simpler to install/maintain, runs nearly all Oracle-syntax SQL as well as ANSI SQL. PPAS has much more JSON capabilities (full CRUD vs. read-only in Oracle), simpler geospatial, simpler / more stable replication and datatypes that match developer expectations, such as BOOLEAN and ENUMs.

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Although the competition between the different databases is increasingly aggressive in the sense that they provide many improvements, new functionalities, compatibility with complementary components or environments, in some cases it requires that it be followed within the same family of applications that performs the company that develops it and that is not all bad, but being able to adapt or configure different programs, applications or other environments developed by third parties apart is what gives PostgreSQL a certain advantage and this diversification in the components that can be joined with it, is the reason why it is a great option to choose.

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The DB is reliable, scalable, easy to use and resolves most DB needs

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• I have no experience with this but from the blogs and news what I believe is that in businesses where there is high demand for scalability, Cassandra is a good choice to go for.
• Since it works on CQL, it is quite familiar with SQL in understanding therefore it does not prevent a new employee to start in learning and having the Cassandra experience at an industrial level.

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• Postgres Plus Advanced Server is quite complex and may take longer to implement certain things than simply using PostgreSQL depending on developer familiarity with the platform.
• Getting up to speed can be daunting so again, there is an upfront cost in time spent learning the platform, besides the potential for extra time spent on a feature-by-feature basis.
• The cost of Postgres Plus Advanced Server should be weighed against simply using PostgreSQL to decide which is the best solution for your business needs.

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• Easy to administer so our DevOps team has only ever used minimal time to setup, tune, and maintain.
• Easy to interface with so our Engineering team has only ever used minimal time to query or modify the database. Getting the data is straightforward, what we do with it is the bigger concern.
• It's free. You can't beat that.

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