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Is MongoDB suitable for time-series data?
MongoDB may be a great non-relational document store, but it just isn’t that great for time-series data. So for time-series data with TimescaleDB, you get all the benefits of a reliable relational database (i.e., PostgreSQL) with better performance than a popular NoSQL solution like MongoDB.
How does MongoDB store time-series data?
If your application requires storing larger data within a single document, such as binary files you may want to leverage MongoDB GridFS. Ideally when storing high volume time-series data it is a best practice to keep the document size small, around 1 disk block in size.
Does MongoDB store data?
In MongoDB, data is stored as documents. These documents are stored in MongoDB in JSON (JavaScript Object Notation) format. JSON documents support embedded fields, so related data and lists of data can be stored with the document instead of an external table. JSON is formatted as name/value pairs.
How do you store time-series data?
Time series data is best stored in a time series database (TSDB) built specifically for handling metrics and events that are time-stamped. This is because time series data is often ingested in massive volumes that require a purpose-built database designed to handle that scale.
How are time series data stored in MongoDB?
As mentioned, we tested two methods for storing time series data in MongoDB. The first, which we’ll refer to as “Mongo-naive,” is straightforward: each time-series reading is stored as a document. So for our given use case (see setup below) of monitoring CPU metrics, the JSON document looks like this:
Who are some companies that use MongoDB?
MongoDB provides all the capabilities needed to meet the demands of a highly performing time-series applications. One company that took advantage of MongoDB’s time series capabilities is Quantitative Investment Manager Man AHL.
How does MongoDB work with Hadoop and spark?
If your data consumers are using tools like Hadoop or Spark, MongoDB has a MongoDB Spark Connector that integrates with these technologies. MongoDB also has drivers for Python, R, Matlab and other platforms used for analytics and data science. Does your organization use BI visualization tools to create reports or analyze the data?
How are time series data used in real time?
With the move from batch to real time systems, the efficient capture and analysis of time-series data can enable organizations to better detect and respond to events ahead of their competitors, or to improve operational efficiency to reduce cost and risk.