Neo4j vs. New Relic

Neo4J is great for creating network graphs or illustrating how things are related. It is also good for finding individuals or things that have greater influence than others in a system. It is not appropriate if you have standard data sets that can be analyzed using conventional methods or visualized using Tableau, for example.

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New Relic its an excellent tool for monitoring services used on the SAAS universe, like web servers, relational and nosql dbms, reverse proxies, text databases, etc. Its also a powerful tool to monitor resource usage on said servers. However, its not well fitted to monitor custom services - if you need to generate alerts based on logs or database information, for example

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• Mature Query language, I found Cypher QL to be mature in handling all sorts of problems we throw at it. Its expressive enough to be intuitive while providing rich features for various scenarios.
• Native support for REST API, that makes interacting with Neo4J intuitive and easy.
• Support for Procedures in Java, procedures are custom code that could be added to the Neo4J to write custom querying of data. The best part about the procedures is it could be invoked using the REST API. This allows us to overcome any shortcomings from their Cypher query language.
• Nice UI and interface for executing the Query and visualizing the response.
• UI access controlled by User credentials allows for neat access controls.
• Awesome free community edition for small-scale projects.

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• It gives us insights of applications, infrastructure, clouds very well.
• The alerting system in New Relic helps us to easily identify the root cause which reduces the MTTR.
• It has new features related to AI which helps to troubleshoot any problem in a very short time it gives future predictions also.

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• One of the hardest challenges that Neo4j had to solve was the horizontal scaling problem. I am not updated on recent developments, but at the time of my use, I couldn't find a viable solution.
• Neo4j does not play with other open source APIs like Blueprint. You have to use the native Neo4j API.
• There wasn't a visual tool to see your data. Of course, third party tools are always available, but I would have loved something which came with the Neo4j bundle. I love that Docker comes bundled with Kitematic, so it's not wrong to hope that Neo4j could also ship with some default visualization software.

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• And while powerful, building tailored dashboards with organ-specific metrics (such as energy load variance across regions) can be difficult to navigate. The UI isn't as drag-and-drop easy, and query-based widgets typically involve some trial and error for non-devs.
• Alerts may be hypersensitive or over general. I We often get a spam of non-critical alerts while doing load testing, all overhauling to me alone and making it difficult to identify actual issues especially in energy systems where spikes are very common.
• With our expanding fleet of Iot devices, the per-host pricing model is becoming expensive, quickly. More detailed billing based on microservices, or that works at sensor level, would make it more adaptable for energy platforms.

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The only issue that we have had with New Relic is that the price might be a little expensive for smaller companies. The amount of data you store in New Relic impacts the cost, and can get away from you if you don't work closely with the vendor. Overall though the application is top notch.

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Learning cypher was super easy coming from a SQL background. Furthermore, the docs Neo4j provides on their website make it really easy to pull up a reference, guide or a quick example. The mac app they provide is also really well designed with good visualisation tools, with the ability to easily use colour, line thickness etc to help navigate your data.

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I have given this much rating as I am used New Relic in different sectors and for different use cases like its K8s monitoring, infra monitoring, full stack monitoring as compare to other tools New Relic gives data in a formatted and connected way, and also it is giving us value for money. It also launches new features day by day which helps users to track the issue very quickly. It also supports OTel integrations which is the latest trend of observability tools. thats why I had given this much rating to New Relic.

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Never observed an outage

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there are times where browser cache will cause issues that require you to clear your browser before continuing.

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The support team has been really helpful and resolved most of the issues on time. However, for a couple of issues, several follow-ups were needed to elicit a reasonable response. The issue was deeply technical and could have been investigated only by their Architects, and bringing them into the ticket took longer than needed

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It's better to start by implementing New Relic in one project and test everything. Try to follow best recommended practices and read all the official documentation. Everything seems well tested. Then, start by installing agents to the rest of your projects and keep a close look to all logs and metrics New Relic gives you.

Neo4j is a graph store and has different use cases compared to another NoSQL Document store like MongoDB. MongoDB is a bad choice when joins are common as existing operators for joining two documents (similar to tables in a relational store) as Mongo 3.5 use SQL like join algorithms which are expensive. MongoDB is a great choice when distributed schemaless rich document structures are important requirements. Cross document transaction support is not native to MongoDB yet, whereas Neo4J is ACID complaint with all its operations.

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Data Dog has solutions that look more attractive, but not at their price point. We have also tried to build a solution straight from the Cloud, where our business is built, but some things are too hard to replicate. This shows that New Relic is useful and helps our efficiency.

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Invited by TrustRadius (TR) on Vendor's Behalf

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info

Agent deployment is easily integrated into our workflow. Adding the agent to new servers is quick and painless

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• Positive: Less complex queries on graph structures, than in relational databases.
• Negative: maintenance is a huge deal, things doesn't work and break, requiring lengthy restore operations.

• We were able to quickly identify our most time consuming APIs. In some cases we were able to bring down times for some apis from 4s to 200ms.
• We were able to identify our slowest database queries and optimize them for quicker response times.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info