Apache Geode vs. SAP HANA Cloud

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

It is well organized. One can use it for the company's portfolio management. Various tasks can be done for managerial purposes. One can track the material from start to end product: for example, raw material, packing material & consumable material to formulated bulk and formulated drug product. This can help to manage spending as well as finding costing of the product.

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

• Real-time reporting and analytics on data: because of its in-memory architecture, it is perfect for businesses that need to make quick decisions based on current information.
• Managing workload with complex data: it can handle a vast range of data types, including relational, documental, geospatial, graph, vector, and time series data.
• Developing and deploying intelligent data applications: it provides various tools for such applications and can be used for machine learning and artificial intelligence to automate tasks, gain insights from data, and make predictions.

• 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

• Requires higher processing power, otherwise it won't fly. How ever computing costs are lower. Incase you are migrating to cloud please do not select the highest config available in that series . Upgrading it later against a reserved instance can cost you dearly with a series change
• Lack of clarity on licensing is one major challenge
• Unless S/4 with additional features are enabled mere migration HANA DB is not a rewarding journey. Power is in S/4

Incentivized

At this moment we are not focusing on SAP, however would love to in the future. This is primarily because of our limited ability to generate more revenue to fund for SAP partnerships and products. Our initial tryst with SAP Partneredge open ecosystem didn't go as planned and we have shelved that for now. Hope we can revive in the future

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

SAP HANA Cloud requires significant expertise on technical side to admin and manage it.It surely is lot of improvement over previous versions of SAPThe modern, role-based SAP Fiori interface has enhanced the user experience for applications like S/4HANA, though the complexity of the underlying database remains. For the average business user, the usability of SAP solutions running on the HANA database has seen a major transformation, largely thanks to the Fiori user interface.

Incentivized

Never contacted support

Incentivized

One specific example of how the support for SAP HANA Cloud impacted us is in our efforts to troubleshoot and resolve technical issues. Whenever we encountered an issue or had a question, the support team was quick to respond and provided us with clear and actionable guidance. This helped us avoid downtime and keep our analytics operations running smoothly.

Incentivized

Professional GIS people are some of the most risk-averse there are, and it's difficult to get them to move to HANA in one step. Start with small projects building to 80% use of HANA spatial over time.

Incentivized

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

Incentivized

I have deep knowledge of other disk based DBMSs. They are venerable technology, but the attempts to extend them to current architectures belie the fact they are built on 40 year old technology. There are some good columnar in-memory databases but they lack the completeness of capability present in the HANA platform.

Incentivized

Limitation of training deliverable by organization

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

• ROI has always been high in terms of the functionality that it offers and the security features it comes with.
• Managing large volumes of data in real-time is not an easy task, but it does it pretty well with faster data processing.

Incentivized