Gavagai vs. PostgreSQL

Gavagai is well suited for a B2C business that receives a lot of customer feedback in a form of open-ended text. It makes life easier for the customer experience team to efficiently identify the strengths and areas of improvement for the business. It saves a lot of time and also the hassle of analysing text data manually. It is not just a word cloud tool that shows you the words with the most number of mentions. Gavagai directs you towards actionability.

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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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• Simplifies text data.
• Lets you customise your dashboard.
• Sentiment analysis
• Supports 47+ languages

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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.

• Auto generated filters based on the data uploaded.
• Adding more Indian regional languages.
• Competitive pricing

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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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As a needed software for day to day development activities

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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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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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I didn't evaluate many options while choosing Gavagai, I had explored a few local vendors whose capabilities were either incomplete or were not up to the mark. Their customer support was also quite poor. Also, the tool was debugged enough which led to frequent crashing. Alchmer although is not a direct competitor to Gavagai, since it's more of a customer feedback tool with additional capabilities of text analytics. I found Alchemer to be extremely expensive. Zonka on the other hand was quite welcoming to feedback from me and promised to develop additional capabilities for my specific requirements although the plan didn't go through due to internal reasons.

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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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• Helps save man hours.
• Reduces the effort required to analyse big data.
• Helps to act upon areas of improvement faster.
• Indicates the strengths or things that are particularly liked by your customers.

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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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