Neo4j, a powerful graph database, enables complex data relationships to be modeled with exceptional performance and flexibility. Exporting this data to a CSV file is a valuable process for a myriad of reasons, such as facilitating the analysis of data within spreadsheet software, where many users can leverage familiar tools to gain insights. In this comprehensive guide, we'll explore the essentials of Neo4j, the step-by-step procedures for exporting your Neo4j database to a CSV file, and the practical use cases for such exports. Additionally, we'll introduce Sourcetable as an innovative alternative to traditional CSV exports for Neo4j. Finally, we'll address common questions and provide clarity on the export process to ensure you have all the information you need to work effectively with your Neo4j data.
Neo4j is an open-source, NoSQL, native graph database that was publicly launched in 2007. It is designed to handle highly connected data and complex queries with ease. As a native graph database, Neo4j implements a true graph model at the storage level, which allows for efficient storage and processing of graph structures.
The database is built with flexibility in mind, providing a full graph stack that includes native graph storage, data science, machine learning, analytics, and visualization capabilities. Its graph storage is backed by vector search, enabling it to scale horizontally to accommodate high-throughputs and very large data sets. Neo4j's architecture is whiteboard-friendly, eliminating the need for tables and joins, which simplifies the data modeling process.
Neo4j is not just a database; it is also a graph analytics platform capable of supporting the development of intelligent applications. It fosters collaboration among developers, data scientists, and innovators, and it has been downloaded over 2 million times, reflecting its popularity and wide adoption. Written in Java and Scala, Neo4j offers a robust query language, Cypher, tailored to intuitively work with graphs.
With support for ACID transactions, cluster support, and runtime failover, Neo4j delivers the reliability required for enterprise usage. It is trusted and utilized by thousands of startups, educational institutions, and large enterprises across various sectors, including financial services, government, energy, technology, retail, and manufacturing. Neo4j's proven track record in production scenarios for large enterprise workloads further demonstrates its capability as a comprehensive solution for graph database needs.
To export data from Neo4j to a CSV file, you must first ensure that the file system export is enabled. By default, this feature is disabled for security reasons. To enable it, you must set apoc.export.file.enabled=true in the apoc.conf configuration file. Once enabled, exported CSV files will be written to the import directory, which is defined by the dbms.directories.import property in your Neo4j configuration.
The apoc.export.csv.graph procedure allows for exporting a virtual graph to a CSV file or as a stream. This procedure is compatible with apoc.export.csv.all and apoc.export.csv.graph when the bulkImport configuration is enabled, which is necessary for creating files suitable for Neo4j Bulk Import. Files generated by these procedures will have specific names that include the input file name as well as labels and relationship types, following the format: [INPUT_FILE_NAME].nodes.[LABEL_NAME].csv and [INPUT_FILE_NAME].relationships.[TYPE_NAME].csv.
If you require exporting your CSV files directly to an Amazon S3 bucket, you must first enable the feature by setting apoc.export.file.enabled=true in apoc.conf, and then restart the database. Additionally, you'll need to download the necessary JAR files for the S3 protocol and place them into the plugins directory. Exporting to S3 involves replacing the file output path with your S3 endpoint. Be aware that the S3 uploading utility may consume up to 2.25 GB of memory during the export process.
For scenarios where writing to a file is not desirable, you can export to a stream. This approach is facilitated by the apoc.export.csv.graph procedure and is useful for integrating export functionality within an application or service without the need for intermediate storage. Streaming can be configured with parameters such as batchSize, delim, arrayDelim, quotes, useTypes, bulkImport, separateHeader, and streamStatements for tailored output.
Integrating your Neo4j database into a spreadsheet no longer requires the cumbersome process of exporting to CSV and then importing into your spreadsheet software. Sourcetable provides a seamless experience that syncs your live data directly from Neo4j into its intuitive spreadsheet interface. This integration not only saves time but also ensures that your data is always up-to-date without any manual intervention.
By using Sourcetable, you can take advantage of its powerful automation features, eliminating the repetitive tasks associated with data export and import. This direct connection to your Neo4j database allows you to perform complex queries just as you would in a traditional spreadsheet, making it an invaluable tool for business intelligence. Moreover, Sourcetable's ability to pull in data from multiple sources concurrently enables you to aggregate and analyze all your information in one place, leading to more informed decision-making.
To export your entire Neo4j database to a CSV file, you can use the apoc.export.csv.all procedure. Remember that by default, exporting to the file system is disabled, so you need to enable it by setting apoc.export.file.enabled=true in the apoc.conf file. The exported CSV file will be written to the import directory, which is defined by the dbms.directories.import property.
Yes, you can export specified nodes and relationships using the apoc.export.csv.data procedure. You will need to provide the details of the nodes and relationships you wish to export. Ensure that exporting to the file system is enabled by configuring the apoc.conf file.
Yes, the apoc.export.csv.query procedure allows you to export the results of a Cypher query to a CSV file or as a stream. If you want to create a bulk import file, this procedure can be used as well, but it only works with apoc.export.csv.all and apoc.export.csv.graph procedures when the bulkImport config is enabled.
The exported CSV file is in a format that is supported by Python and R data science libraries, making it compatible for use with various data science tools. The export procedures provide the data in a structured format that can be easily imported into these libraries for analysis.
When the bulkImport configuration is enabled, apoc.export.csv.query, apoc.export.csv.all, and apoc.export.csv.graph create a list of files specifically formatted for Neo4j Bulk Import. Node files are named in the format [INPUT_FILE_NAME].nodes.[LABEL_NAME].csv and relationship files are named [INPUT_FILE_NAME].relationships.[TYPE_NAME].csv.
Exporting data from Neo4j to CSV is a versatile process that caters to the needs of sharing query results, importing data into other tools, and facilitating the use of Python and R data science libraries. Whether you require exporting the entire database, specific nodes and relationships, or the results of a Cypher query, the APOC library's export CSV procedures provide robust solutions, with the ability to export as files or streams and support for bulk import configurations. However, if your goal is to streamline the integration of Neo4j data into your workflows even further, consider using Sourcetable to import data directly into a spreadsheet. Sign up for Sourcetable to bypass the traditional export process and get started with enhanced data management today.