NoSQLBooster

What is NoSQLBooster ?

The smartest IDE for MongoDB

NoSQLBooster for MongoDB is a shell-centric cross-platform graphical interface tool for MongoDB, which provides comprehensive server monitoring tools, fluent query builder, SQL query, query code, esnext support task scheduling, and true IntelliSense Experience.

Why choose NoSQLBooster for MongoDB?

NoSQLBooster for MongoDB offers the true IntelliSense experience. The integrated language service knows all the conclusions, methods, properties, variables, possible keywords, even collection names, field names, and MongoDB operators. IntelliSense suggestions appear as you type. You can always trigger it manually with Ctrl-Shift-Space. Out of the box, Ctrl-Space, Alt-Space are acceptable triggers.

• In the script editor, parameter hints appear as you type a method call.
• We offer tons of integrated snippets, useful date range snippets, SQL conversion snippets for MongoDB...
• Mouse passing shows lots of useful information, such as symbol types, function definition, information type, and document.
• The corresponding brackets are highlighted as soon as the cursor is close to one of them.

See MongoDB with SQL

With NoSQLBooster for MongoDB, you can run SQL SELECT Query in MongoDB. SQL support includes SQL JOINS, functions, expressions, aggregation for collections with nested objects and arrays.

Let's look at how to use the GROUP BY clause with the SUM function in SQL.

Instead of writing the MongoDB query, which is represented as a JSON-like structure

SQL query features

• Access data via SQL, including WHERE, ORDER BY, GROUP BY, HAVING, DISTINCT, LIMIT filters
• SQL functions (COUNT, SUM, MAX, MIN, AVG)
• Date, String, Conversion Functions (dateToString, toUpper, split, substr ...)
• Aggregation pipeline operators as SQL functions
• EQUI JOIN SQL and uncorrelated subqueries
• Provides a programming interface (mb.runSQLQuery) that can be integrated into your script
• Autocomplete for keywords, MongoDB collection names, field names, and SQL functions

Monitor and adjust performance

NoSQLBooster provides rich monitoring and performance analysis tools to help you keep your MongoDB environment running without problems.

• Visual Explain Plan transforms the explanation output into a hierarchical view, allowing query tuning to improve the query and resolve performance issues.
• Real-time server status (mongostat), view MongoDB's real-time performance metrics as a graph or tabular format.
• Operations viewer in progress, find and eliminate long-running MongoDB operations quickly.
• MongoDB Log Parser, easier to analyze, filter and analyze MongoDB log information.
• Database Profiler, collects detailed information about database commands executed on a running mongod instance.
• GUI to mongotop, tracks the time required to read and write operations completely.
• Resolve replica sets issues

Learn Mongodb with Interactive Samples

The "My Queries" tab is used to quickly open user-saved query scripts. By default, the user-saved query script is saved as a "connection -> -database > query name" directory structure. Double-click to open a saved query script that will automatically connect to the appropriate database server and switch to the appropriate database.

The "Samples" tab includes several Tutorials enabled for NoSQLBooster. All samples are already executable in NoSQLBooster, with detailed descriptions. You can try these queries and change them to learn better.

Fluent MongoDB Query Constructor

NoSQLBooster for MongoDB supports the mongoose-like fluent query builder API. A query allows you to create a query using threadsyntax, rather than specifying a JSON object. The aggregation structure is now also fluent. You can use it as currently documented or through chained methods.

Schema Analyzer

Schema Analyzer is a useful internal tool. Because of schemaless features, collections in MongoDB do not have a schema document to describe the field data type, collection structure, and validations. With our new Schema Analyzer tool, you get a document to describe the schema of a specific collection of N sampled records (random, first, last) or all records.

The document shows the probability of sampled objects, different types of percentages, and you can get a summary of the specific collection schema. If you want a more accurate result, you can show more records or parse the entire collection, but it can take a long time to finish if the collection has millions of records or thousands of fields.

It also shows the validation of collection documents, which is a new feature in MongoDB 3.2. There is a validator window displayed below the document. If you click the link, the field is highlighted in the window.

You can export this document to the most popular document file types, such as MS Word, PDF, HTML, along with JSON, TXT, and CSV. Mongoose schema file.js supported as well.

Shell Extensions, Using Node Modules, Lodash, Momentjs in Your Script

NoSQLBooster for MongoDB is an electron-powered desktop application that groups Node.js and Chromium runtime. You can use any integrated Node global objects and modules.js (console, util, fs, path ...) and pure JS NPM packages in NoSQLBooster for MongoDB. It also adds a fluent API similar to mongoose, provides the mb.runSQLQuery function, integrates some utility modules (lodash, moment, bluebird, shelljs, mathjs) into the global scope to make life within the MongoDB script a little easier.

System requirements:

CPU: 1.8 GHz dual core processor

RAM: 2 GB

HDD / SSD: 50 GB of free space on the main drive

Operating system: Microsoft Windows 8 32-bit, Microsoft Windows 7 32-bit and Microsoft Windows Vista 32-bit

Resolution: 1024×768