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How to Convert CSV to NDJSON

Transform comma-separated data into Newline Delimited JSON for streaming, data pipelines, and modern data systems

Step 1

Input Your CSV Data

Paste your CSV data with headers in the first row. Each subsequent row will become a JSON object on its own line in the NDJSON output.

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Paste directly: Copy CSV from spreadsheets, database exports, or BI tool downloads
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Upload a file: Click "Upload" to select a .csv or .txt file
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Try the sample: Click "Sample" to see a working conversion example

Example: CSV Input (Employee Records)

A standard CSV export from a spreadsheet or HR system — the first row defines the column headers:

name,department,salary,active
Alice Johnson,Engineering,95000,true
Bob Smith,Marketing,72000,true
Charlie Lee,Support,58000,false
Diana Ross,Engineering,102000,true

The converter will map each column header to a JSON key and infer data types automatically.

Step 2

Automatic NDJSON Generation

The converter automatically processes your CSV (RFC 4180) and creates properly structured JSON Lines:

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Header mapping: First row headers become JSON object keys for every output record
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Type inference: Numbers, booleans (true/false), and null are automatically detected and typed — no manual casting needed
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Quoted field support: CSV fields with commas, double quotes, or newlines are properly handled per the RFC 4180 standard
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One line per row: Each CSV data row becomes exactly one JSON object in the output — maintaining the 1:1 relationship

Example: NDJSON Output

Each CSV row becomes a JSON object on its own line — numeric and boolean types are inferred automatically:

{"name":"Alice Johnson","department":"Engineering","salary":95000,"active":true}
{"name":"Bob Smith","department":"Marketing","salary":72000,"active":true}
{"name":"Charlie Lee","department":"Support","salary":58000,"active":false}
{"name":"Diana Ross","department":"Engineering","salary":102000,"active":true}

salary is typed as a number (95000, not "95000") and active is typed as a boolean — ready for direct ingestion into APIs.

Step 3

Export Your NDJSON

Get the NDJSON output ready for your data pipeline, streaming system, or application:

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Copy to clipboard: Paste into your application, API testing tools like Postman, or shell scripts
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Download as .ndjson: Save as a file for data streaming, Kafka producers, log ingestion, or batch processing
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Streaming-ready format: NDJSON is the standard for Elasticsearch bulk indexing, Kafka message queues, and log shipping systems

What is CSV to NDJSON Conversion?

CSV to NDJSON conversion transforms tabular CSV (Comma-Separated Values) data into Newline Delimited JSON — one JSON object per line. This is essential when migrating from traditional spreadsheet-based workflows to modern streaming data architectures.

The conversion process reads each CSV row, maps column headers to JSON keys, and infers data types for numbers, booleans, and null values. The result is a JSON Lines file ready for direct ingestion into the Elasticsearch Bulk API, Google BigQuery streaming inserts, or Apache Kafka producers.

Unlike converting to a JSON array, NDJSON output is streamable — each line can be processed independently as it arrives, making it far more memory-efficient for large datasets. This is why data systems like Elasticsearch and BigQuery prefer NDJSON over standard JSON arrays for bulk data loads.

Frequently Asked Questions

How does CSV to NDJSON conversion work?

The first row of your CSV is used as column headers (JSON keys). Each subsequent row becomes a JSON object on its own line, following the NDJSON specification, with values mapped to the corresponding header keys.

Are data types preserved?

Yes. The converter automatically detects numbers (integers and decimals), booleans (true/false), and null values. Remaining values are kept as strings. This gives you properly typed JSON output — salary becomes 95000, not "95000".

What about CSV fields with commas or quotes?

The converter follows the RFC 4180 standard for CSV parsing. Fields containing commas, double quotes, or newlines should be enclosed in double quotes. Quotes within fields are escaped with double quotes ("").

Why use NDJSON instead of a JSON array?

NDJSON is streamable — each line can be processed as it arrives without loading the entire file into memory. This makes it far more efficient for large datasets. Systems like Elasticsearch, Google BigQuery, and Apache Kafka prefer NDJSON for bulk operations.

What streaming tools accept NDJSON output?

The Elasticsearch Bulk API, Google BigQuery streaming inserts, Apache Kafka producers, MongoDB mongoimport, AWS Kinesis Data Firehose, and log shipping agents like Logstash and Fluentd all accept NDJSON natively.

Can I convert NDJSON back to CSV?

Yes — use our NDJSON to CSV converter to go in the other direction. You can also view your NDJSON as a sortable table or convert it to a standard JSON array.

Is this converter free?

Yes, completely free with no limits. All processing happens in your browser — your data never leaves your device.

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