Apache Geode vs. Data Virtuality Platform

The biggest advantage of using Apache Geode is DB like consistency. So for applications whose data needs to be in-memory, accessible at low latencies and most importantly writes have to be consistent, should use Apache Geode. For our application quite some amount of data is static which we store in MySQL as it can be easily manipulated. But since this data is large R/w from DB becomes expensive. So we started using Redis. Redis does a brilliant job, but with complex data structures and no query like capability, we have to manage it via code. We are experimenting with Apache Geode and it looks promising as now we can query on complex data-structures and get the required data quickly and also updates consistent.

Incentivized

Data Virtuality Platform's best and most unique feature is
that it is SQL-based, giving us flexibility when working with our data that
other marketing integration pipeline tools couldn't provide. Our main benefits
are the short time it takes to connect to our data sources and the flexibility
of the virtual SQL layer to meet our end users' data needs. It paves the way
for us to tap into various data repositories, extract the data contained
within, and examine it. It allows us to access information, generate actionable
reports, and make data-driven decisions. However, inadequate data governance
rules and a complex configuration process make data connectors challenging.

Incentivized

• Super Fast data pull/push
• Provided ACID transactions, so it works like a SQL Database
• Provides replication & partitioning, so our data is never lost and extraction is super fast. NoSql like properties

Incentivized

• ETL/ELT model building is flexible.
• The pipes' setup and use are intuitive.
• It lets us access various data sources, extract, and analyze data.

Incentivized

• Needs more supporting languages. Out of box Python, Nodejs adapters would be wonderful
• Currently it supports just KV Store. But if we could cache documents or timeseries data would be great
• Needs more community support, documentation.

Incentivized

• Configuring data connectors can be tricky.
• Price could be more flexible and adapt to the use case.
• The ETL builder's user interface could be prettier.

Incentivized

Still Experimenting. Initial results are good. we need to figure out if we can completely replace Redis. Cost wise if it makes sense to keep both or replacement is feasible.

Incentivized

Never contacted support

Incentivized

Still Experimenting. But looks promising as it has query capabilities over complex data structures

Incentivized

Data Virtuality Platform has powerful transformation and
scheduling capabilities combined with the best support team. A virtual data
layer that supports SQL procedures is a game changer. Data Virtuality has made
data management more efficient. It lets us access various data sources, extract,
and analyze data. The short time it takes to connect to our data sources and
the flexibility of the virtual SQL layer allows us to meet our end users' data
needs.

Incentivized

• Still experimenting so difficult to quote
• For a small size project/teams might be an overkill as it still has certain learning curve
• For Medium to large projects with complex Data Structures that need to be queried with a fast o/p it definitely works

Incentivized

• It has the capability of integrating data from a variety of different sources.
• It improved development and user interface to offer a robust MDM repository and strategy.
• It offers a comprehensive solution for processing and retrieving data, which is one of the ways it assists.

Incentivized