PostgreSQL (alternately Postgres) is a free and open source object-relational database system boasting over 30 years of active development, reliability, feature robustness, and performance. It supports SQL and is designed to support various workloads flexibly.
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 …
My expirence with other solutions is very limited, but what I saw/heard is, that on Azure the managed MS SQL Server is said to be more flexible and you can use it in a serverless-ish fashion. But on the other hand, PostgresSQL is still strong regarding its efficiency. And in my …
Being open source, PostgreSQL offers the highest performance among its peers. It has a strong support community where we can find solutions to most of the queries. It's suited for GIS (Geospatial) based applications, making it unique from its peers. There are fewer databases …
PostgreSQL holds it own against both these options. Some of these DBs are in play for certain needs but the majority are PostgreSQL because of cost and operational performance.
In my experience using all of these products over many years, PostgreSQL is better than any of them in reliability, performance, productivity, cost, scalability and interoperability across operating systems.
MySQL is an Oracle product which has in itself some known issues due to that (support, contract terms). Based on my knowledge, PostgreSQL support everything that MySQL support (syntax wise) and it adds more improvements and syntaxes that make the life of database engineers and …
First It's open source and it's cost-effective compared to other databases.PostgreSQL can be easily integrated with numerous platforms. It is well known and appreciated so relying on it as our system database can be easily accepted by our customers. And if your developing a …
For our use cases, PostgreSQL is just as feature rich as other options, costs less, and is simple to get up and running. There is also a plethora of documentation to support it which makes it a great option for a small scale startup without needing high levels of expertise to …
In this case, Postgres is preferred because it handles large data sets and requires fewer hardware resources than its competitor, MySQL. Compared to PostgreSQL, Microsoft products are excellent, but the installation process for MS SQL is lengthy. PostgreSQL has an advantage …
I've been using different databases for the past 20 years, solutions like MS SQL Server, MySQL, MariaDB, Interbase, Firebird, DB2, etc., and by using them I wasn't able to be neither close to the performance PostgreSQL deliver. Also, it is one of the most popular databases on …
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 …
We evaluated both PostgreSQL and MySQL, two popular open source relational databases. While they are very similar in most areas, PostgreSQL's reliability and performance won us over, plus it has much better support from cloud vendors we also work with.
Postgres stacks up just [fine] along the other big players in the RDBMS world. It's very popular for a reason. It's very close to mySQL in terms of cost and features - I'd pick either solution and be just as happy. Compared to Oracle it is a MUCH cheaper solution that is just …
A free corporate professional product. Who does not want to have such a thing, we hesitated because we did not know the product before and frankly we did not want it at first. But when we give it a chance, it has been running smoothly for years.
When we were originally evaluating Redshift we ran into some issue with dates. Either way, Postgres is a better choice than Redshift because it avoids vendor lockin. We ended up choosing Postgres over MySQL because it was easier at the time to get a hosted Postgres cluster up …
As I have been telling all along, PostgreSQL is much cheaper compared to the other RDBMS solutions. It has got better performance with some of the application services that we are using and is easy to maintain. Overall, we are satisfied migrating to PostgreSQL database clusters.
Much more mature and stable when compared to MySQL with features such as MVCC, complex subquery plans, ORDBMS, and NoSQL support. With Oracle retaining rights to MySQL its future as an open database is less secure and is no longer in the hands of the community. PostgreSQL also …
Its main characteristic is the integrity of the data. In addition, being free software, it has no costs associated with its license, which allows the number of installations to be scaled without problems.
The technical staff quickly learns about its installation, configuration …
Both Oracle and MS-SQL database option fell when we evaluated the effect on our overall solution cost to our customers. customer examine the overall cost of the solution they buy, selecting Oracle or MS-SQL would leave less money in our pockets. We are Linux based solutions and …
PostgrPostgreSQL as a transaction db engine against oracle and sql server works well. TPM wise compared to MySQL and MariaDB, on an evan scale. SQL function supports, far outweighs compared to MySQL and MariaDB. PG Extensions allow for flexibiltity and scalability. Allows …
We selected PostgreSQL due to the number of employees who have used it in the past. The data consistency guarantees. The multiple transaction isolation levels support.
PostgreSQL outperforms every other option. It is faster, more flexible, more reliable, easier to maintain, and more consistent in behaviour than any of the other offerings.
The main reason for select PostgreSQL against MS SQL Server Express edition is the necessity to use open-source platform, without any issues for licensing, client licensing, etc. etc, which is usually follows developers and project managers when they start to use products and …
Apache Cassandra and PostgreSQL (or Postgres) are popular open-source databases; Apache Cassandra is NoSQL and boasts high availability. PostgreSQL is an object-relational database and overall one of the world’s most adopted database management systems after only MySQL, Oracle, and Microsoft SQL Server. Cassandra is available free under the Apache License 2.0 and PostgreSQL is free under the liberal PostgreSQL License, which is similar to the BSD or MIT licenses.
PostgreSQL and Cassandra are frequently compared but not necessarily competitors as each is suitable for different use cases. PostgreSQL is deployed at companies of all sizes and enterprises, while Cassandra is more often deployed at larger companies and enterprises given its focus on helping users manage large volumes of possibly unstructured data across multiple data centres.
Features
There are differing reasons to deploy either Apache Cassandra or PostgreSQL for a project.
Cassandra is a wide column store suitable for supporting high velocity read and write. It is liked for its core competency, which in its case is scalability and availability. Other advantages users point out is that it is low maintenance, able to perform well on low cost commodity hardware, and that CQL (Cassandra Query Language) is easy to use, being somewhat similar to SQL.
PostgreSQL, unlike Cassandra, is an object-relational database that is typically associated to BI & analytics use cases, and supports sometimes needed complex design with seldom used but powerful features like function overloading and table inheritance. PostgreSQL is popular for a reason: users get, for free and with great open source community support, a highly programmable, feature-rich, fast, JSON & geospatial mapping capable, easy to implement, and all-around good at everything database.
Limitations
For specific use cases, there are reasons to go in a different direction than building with a Cassandra or PostgreSQL database. Drawbacks are somewhat similar, though through the looking glass of comparing a SQL database vs. a NoSQL database.
As a key-value store users note that Cassandra can be inefficient and not as performant as alternatives, and also state that queries that are ad-hoc and don’t closely mirror the database’s particular design process will tend to not work well, or may be impossible. For this reason, users stress that competent data modeling and a basic understanding of NoSQL is a must when working with Cassandra: get an expert to set it up, or risk learning to become an expert by getting it all wrong.
PostgreSQL’s features are powerful, and for inexperienced developers can lead to disastrous, anti-performant design, and it is generally less performant than MySQL, which is why that database is preferred for use cases like powering websites or running simple queries. Also, it lacks in-memory caching. Finally, many users say it can be hard to get started, with a steep learning curve and somewhat lacking documentation.
Pricing
Apache Cassandra and PostgreSQL are open source and both are available at no cost to the user when self-hosted. Cloud hosting may be desirable, in which case pricing will depend on compute costs set by the third-party cloud providers (e.g. the Amazon Keyspaces Cassandra DBaaS, etc.) or managed hosting providers: for example Instaclustr and Aiven, among others, offer managed Cassandra; and, managed PostgreSQL is provided by, to name a few, DigitalOcean, ScaleGrid Aiven.
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.
Based on my experience, PostgreSQL is exactly what I imagine when thinking of a relational database: it is fast for querying and intuitive (if the underlying relations have been well written) and its writes are also efficient. Of course you need to know that a relational database is what you need, for example I would not recommend it if you have a lot of unstructured data that have no way to create a relation from and if you need to run heavy aggregations over your data, as it is not where PostgreSQL would shine.
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.
The stability it offers, its speed of response and its resource management is excellent even in complex database environments and with low-resource machines.
The large amount of resources it has in addition to the many own and third-party tools that are compatible that make productivity greatly increase.
The adaptability in various environments, whether distributed or not, [is a] complete set of configuration options which allows to greatly customize the work configuration according to the needs that are required.
The excellent handling of referential and transactional integrity, its internal security scheme, the ease with which we can create backups are some of the strengths that can be mentioned.
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.
The query syntax for JSON fields is unwieldy when you start getting into complex queries with many joins.
I wish there was a distinction (a flag) you could set for automated scripts vs working in the psql CLI, which would provide an 'Are you sure you want to do X?' type prompt if your query is likely to affect more than a certain number of rows. Especially on updates/deletes. Setting the flag in the headless(scripted) flow would disable the prompt.
Better documentation around JSON and Array aggregation, with more examples of how the data is transformed.
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.
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.
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.
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.
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.
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!
In my experience using all of these products over many years, PostgreSQL is better than any of them in reliability, performance, productivity, cost, scalability and interoperability across operating systems.
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.