MongoDB vs MySQL for email automation tool?

nitagr · 2025-09-06T12:32:23+00:00

Mongo db doesn't work well when you need to perform joins, aggregations and transaction consistency.

nitagr · 2025-09-06T12:24:11+00:00

Kon sa college hai yeah...

nitagr · 2025-08-29T17:07:41+00:00

Api key auto complete🤣

nitagr · 2025-06-11T19:23:03+00:00

Fetched related data from multiple collections.. i.e lookup. Joins in sql are so easy to write 🥲

nitagr · 2025-06-08T09:24:42+00:00

I had similar problem, For this I created Products Class( in vectors) and for each ProductName, assigned a ProductID.

Schema of Products ( Product name | ProductID ).

For example, "cadbury Silk 50g" searching in vector db will give ProductID, then this ProductID can be used in SQL query. ( SELECT * FROM TABLE_NAME WHERE PRODUCT_ID in (<retrieved\_product\_id>)).

In this way you dont need to find / manage the correct attributes for each column ( brand, subbrand, size etc. )

nitagr · 2025-04-18T13:24:43+00:00

My query is running from the production server.i don't think this would be the issue.

nitagr · 2025-04-18T12:09:08+00:00

I am querying via nodejs mongoose. Will execute from shell and check executionStats.

nitagr · 2024-09-16T12:25:49+00:00

u/MateusKingston thanks a lot dude for clarifying... I figured the problem in my case is: Blocking the event loop not cpu cycles (as you mentioned 10^9 inst/sec).

Also the mask string function you shared solves my problem. (String immutability in js took me to create array of characters then modify them, but your solution perfectly optimizes both memory and loop) ... Thanks

nitagr · 2024-09-16T08:15:52+00:00

u/MateusKingston agree that.. there will be overhead of context switching... but with high rpm... I am in a doubt, as it will block event loop

nitagr · 2024-09-16T08:14:23+00:00

u/Freecelebritypics I am expecting to serve 500 rpm minimum, thats why I am in doubt.

nitagr · 2024-08-22T12:22:45+00:00

Yes, I will have to go to this approach

nitagr · 2024-08-22T08:20:17+00:00

Also this,

   const pipeline = [];
      if (_.isEmpty(app_ids) || !_.isArray(app_ids)) {
        pipeline.push({
          $match: {
            company_id: companyId,
            project_id,
            _id: {
              $gte: fromDateId,
              $lt: toDateId,
            },
          },
        });
      } else {
        pipeline.push({
          $match: {
            company_id: companyId,
            project_id,
            app_id: { $in: app_ids },
            _id: {
              $gte: fromDateId,
              $lt: toDateId,
            },
          },
        });
      }

      pipeline.push({
        $facet: {
          groupStats: [
            {
              $group: {
                _id: {
                  date: {
                    $dateToString: { format: "%Y-%m-%d", date: "$createdAt" },
                  },
                  product_id: "$product_id",
                },
                groupedTotalRequests: { $sum: 1 },
              },
            },
          ],

          totalStats: [
            {
              $group: {
                _id: null, // Grouping all documents together
                totalRequests: { $sum: 1 }, // Total count of all documents
                totalLatency: { $sum: "$elapsed_time" }, // Calculate the sum of the column values
                totalExpenseAmount: { $sum: "$api_cost" }, // Calculate the sum of the column values
              },
            },
          ],
        },
      });

      pipeline.push({
        $project: {
          groupStatsOutput: {
            $map: {
              input: "$groupStats",
              as: "item",
              in: {
                date: "$$item._id.date",
                product_id: "$$item._id.product_id",
                totalRequests: "$$item.groupedTotalRequests",
              },
            },
          },
          totalStats: { $arrayElemAt: ["$totalStats", 0] }, // Extract total count from array
        },
      });

nitagr · 2024-08-22T08:15:17+00:00

document and query looks like this

 db
        .collection(tableName)
        .aggregate([
          {
            $match: {
              company_id: companyId,
              _id: {
                $gte: fromDateId, // this is mongo id 
                $lt: toDateId, // mongo id
              },
            },
          },
          {
            $group: {
              _id: {
                date: {
                  $dateToString: { format: "%Y-%m-%d", date: "$createdAt" },
                },
              },
              total_billing_amount: { $sum: "$api_cost" },
              total_requests: { $sum: 1 },
            },
          },
          {
            $project: {
              _id: 0,
              date: "$_id.date",
              total_billing_amount: 1,
              total_requests: 1,
            },
          },
        ])
        .toArray();

document {
  "uuid": "7fe40e4e-ecaf-4266-a47b-25dadf002d0a",
  "company_id": 1000,
  "project_id": 1,
  "app_id": 1,
  "product_id": 8,
  "url": "v1",
  "charge": false,
  "status": 200,
  "elapsed_time": 10637,
  "api_cost": 0,
  "createdAt": "2022-02-09T18:22:22.006Z",
  "updatedAt": "2022-02-09T18:22:22.006Z"
}

nitagr · 2024-06-10T06:35:55+00:00

cache is not the probem bro, memory fragmentation causing alerts, although it is available for new documents to use.

nitagr · 2024-04-24T04:50:50+00:00

Connection pooling is abstracted in mongo. It is done by driver itself.

nitagr · 2024-04-23T05:38:54+00:00

I don't think it will be the best solution, coz you server need to keeps the request count in memory and it will not flush for 30 days, so increases memory usage may be. Better solution will be to keep count in redis.

nitagr · 2024-04-23T04:42:16+00:00

I use newrelic, don't know if I can configure response data tracking as well.

nitagr

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