Apache Cassandra vs. MongoDB vs. Zscaler Internet Access

Apache Cassandra is a NoSQL database and well suited where you need highly available, linearly scalable, tunable consistency and high performance across varying workloads. It has worked well for our use cases, and I shared my experiences to use it effectively at the last Cassandra summit! http://bit.ly/1Ok56TK It is a NoSQL database, finally you can tune it to be strongly consistent and successfully use it as such. However those are not usual patterns, as you negotiate on latency. It works well if you require that. If your use case needs strongly consistent environments with semantics of a relational database or if the use case needs a data warehouse, or if you need NoSQL with ACID transactions, Apache Cassandra may not be the optimum choice.

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If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.

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It's best suited for a distributed remote workforce, securing internet access for users from anywhere. Suitable for highly regulated industries, such as banking and Healthcare. Not a good fit for an organisation where most of its legacy is in an on-premises environment. Bandwidth-intensive industries like media/entertainment firms.

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• Continuous availability: as a fully distributed database (no master nodes), we can update nodes with rolling restarts and accommodate minor outages without impacting our customer services.
• Linear scalability: for every unit of compute that you add, you get an equivalent unit of capacity. The same application can scale from a single developer's laptop to a web-scale service with billions of rows in a table.
• Amazing performance: if you design your data model correctly, bearing in mind the queries you need to answer, you can get answers in milliseconds.
• Time-series data: Cassandra excels at recording, processing, and retrieving time-series data. It's a simple matter to version everything and simply record what happens, rather than going back and editing things. Then, you can compute things from the recorded history.

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• Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
• You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
• Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.

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• Single Pane of Glass Management - Everything is very easy to access and monitor the entire environment from an internet security perspective.
• Install Flexibility - We can and do install Zscaler Internet Access on both our client devices as well as our SD-WAN appliances and servers. This allows us to control internet security even on devices without an agent in our networks.

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• Cassandra runs on the JVM and therefor may require a lot of GC tuning for read/write intensive applications.
• Requires manual periodic maintenance - for example it is recommended to run a cleanup on a regular basis.
• There are a lot of knobs and buttons to configure the system. For many cases the default configuration will be sufficient, but if its not - you will need significant ramp up on the inner workings of Cassandra in order to effectively tune it.

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• An aggregate pipeline can be a bit overwhelming as a newcomer.
• There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
• Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.

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• The logs feel kind of lack luster
• When issues are arising with SSL Inspection, logs show everything working despite end user experience
• Could use some kind of global find functionality or something that would allow you to search the entire configuration for matching URLs and the like

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I would recommend Cassandra DB to those who know their use case very well, as well as know how they are going to store and retrieve data. If you need a guarantee in data storage and retrieval, and a DB that can be linearly grown by adding nodes across availability zones and regions, then this is the database you should choose.

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I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.

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While Zscaler Internet Access (ZIA) delivers critical value in cloud security and RBI compliance, I rate renewal likelihood 7/10 due to evolving needs versus platform limitations. Below is my rationale:

Key Gaps:

1. Advanced Threat Costs:

ZIA’s add-ons (e.g., Advanced DLP, Sandboxing) incur 35%+ cost premiums – straining budgets as transaction volumes (UPI/iMobile) grow 50% YoY.

2. API Banking Scalability:

ZIA’s API rate limits throttle real-time policy sync during UPI peaks (10K+ TPS), forcing workarounds for finacle integrations.

3. RBI Future-Proofing:

Limited native support for upcoming digital rupee (CBDC) security rules requires custom development, increasing compliance overhead.

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It’s great tool but it can be complicated when it comes administration and maintenance.

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NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.

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The application is easy to install and configure on all Windows devices. To troubleshoot any internet issue, we can easily collect all the relevant logs from Zscaler and check the exact issue. The only problem is with the uninstall, as a dedicated crew needs to provide the password.

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There are often performance issues reported

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Sometimes instead giving straight answer, we ‘re getting transfered to talk professional service.

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Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.

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Zscaler's ZIA support is quick and knowledgable. They respond within 1-2 hours of you submitting your ticket. They are very thorough and are typically ready to jump on a live troubleshooting session. Our ZIA platform and how we use is it unique so at times tickets can be open for weeks but we alway get quality support compared to other unrelated product support in our enterprise

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While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.

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We evaluated MongoDB also, but don't like the single point failure possibility. The HBase coupled us too tightly to the Hadoop world while we prefer more technical flexibility. Also HBase is designed for "cold"/old historical data lake use cases and is not typically used for web and mobile applications due to its performance concern. Cassandra, by contrast, offers the availability and performance necessary for developing highly available applications. Furthermore, the Hadoop technology stack is typically deployed in a single location, while in the big international enterprise context, we demand the feasibility for deployment across countries and continents, hence finally we are favor of Cassandra

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We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.

Zscaler Intenet Access outperformed the competition due to its lightning-fast policy delivery and cross-compatibility. It is easy to track employee usage and block unnecessary websites, reducing company internet usage. Zscalar installed on every system increases cloud-based software bandwidth, decreasing user turnaround time and increasing efficiency.

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• I have no experience with this but from the blogs and news what I believe is that in businesses where there is high demand for scalability, Cassandra is a good choice to go for.
• Since it works on CQL, it is quite familiar with SQL in understanding therefore it does not prevent a new employee to start in learning and having the Cassandra experience at an industrial level.

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• Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
• You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB

• Has allowed us to remove other products that were suboptimal
• Saved us money overall by stacking it with other Zscaler products
• Created a more secure work environment for our users through intelligent internet policies that are not needlessly restrictive while still maintaining security best practices

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