Apache Hive vs. Azure Cosmos DB vs. PostgreSQL

Software work execution is on a large scale, it is good to use for new projects or organizational changes, data lineage mapping has always been dubious but this one has had good results. You can store and synchronize data from different departments, the storage process can be manual but it is best automated.

Incentivized

Like any NoSQL database, whether it's MongoDB or not, it's best suited for unstructured data. It's also well suited for storing raw data before processing it and performing any type of ETL on the data.

Incentivized

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.

Incentivized

• Apache Hive allows use to write expressive solutions to complex problems thanks to its SQL-like syntax.
• Relatively easy to set up and start using.
• Very little ramp-up to start using the actual product, documentation is very thorough, there is an active community, and the code base is constantly being improved.

Incentivized

• Scalable Instantly and automatically serverless database for any large scale business.
• Quick access and response to data queries due to high speed in reading and writing data
• Create a powerful digital experience for your customers with real-time offers and agile access to DB with super-fast analysis and comparison for best recommendation

Incentivized

• 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.

• Some queries, particularly complex joins, are still quite slow and can take hours
• Previous jobs and queries are not stored sometimes
• Switching to Impala can sometimes be time-consuming (i.e. the system hangs, or is slow to respond).
• Sometimes, directories and tables don't load properly which causes confusion

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• Expensive, so be careful of the use case.
• We had a thought time migrating from traditional DBs to Cosmos. Azure should provide a seamless platform for the migration of data from on-premises to cloud.

Incentivized

• 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

Incentivized

Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.

It's efficient, easy to scale, and works. We do have to do a bit of administration, but less now than when we started with this a couple of years ago. Microsoft continues to improve its self-management capability.

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As a needed software for day to day development activities

Incentivized

Hive is a very good big data analysis and ad-hoc query platform, which supports scaling also. The BI processes can be easily integrated with Hadoop via the Hive. It can deal with a much larger data set that traditional RDBMS can not. It is a "must-have" component of the big data domain.

Incentivized

It has very good compatibility and adaptability with other APIs and developers can safely create new apps because it is compatible with various tools and can be easily managed and run under the cloud, and in terms of security, it is one of the best of its kind, which is very powerful and excellent.

Incentivized

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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Apache Hive is a FOSS project and its open source. We need not definitely comment on anything about the support of open source and its developer community. But, it has got tremendous developer support, awesome documentation. I would justify the fact that much support can be gathered from the community backup.

Incentivized

Microsoft is the best when it comes to after-sales support. They have a well-structured training and knowledge base portal that anyone can use. They are usually quick to respond to cases and are on point for on-call support. I have no complaints from a support standpoint. Pretty happy with the support.

Incentivized

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.

Incentivized

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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Besides Hive, I have used Google BigQuery, which is costly but have very high computation speed. Amazon Redshift is the another product, I used in my recent organisation. Both Redshift and BigQuery are managed solution whereas Hive needs to be managed

Incentivized

Cosmos DB is unique in the industry as a true multi-model, cloud-native database engine that comes with solutions for geo-redundancy, multi-master writes, (globally!) low latency, and cost-effective hosting built in. I've yet to see anything else that even comes close to the power that Cosmos DB packs into its solution. The simplicity and tooling support are nice bonus features as well.

Incentivized

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.

Incentivized

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

Incentivized

• Apache hive is secured and scalable solution that helps in increasing the overall organization productivity.
• Apache hive can handle and process large amount of data in a sufficient time manner.
• It simplifies writing SQL queries, hence helping the organization as most companies use SQL for all query jobs.

Incentivized

• It's made managing raw data much easier
• It provides a way to maintain raw data at a low cost
• It's easy to massage the data

Incentivized

• 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.

Incentivized