Apache Arrow is an open-source framework that enables efficient in-memory columnar data representation, facilitating interoperability among various processing engines. It was developed by several open-source leaders, including Wes McKinney, creator of Pandas, to solve the problem of making Pandas interoperable with data processing systems. Apache Arrow provides zero-copy reads, reducing memory requirements and CPU cycles, and is designed for modern CPUs and GPUs to process data in parallel. Several companies, including InfluxDB, use Apache Arrow as a critical component in their architecture, such as converting Pandas DataFrames to Spark DataFrames or storing time series data efficiently. The framework has been widely adopted due to its efficient columnar memory exchange, and its builders have made significant contributions to other open-source projects, including Fast, memory-efficient sorts, performance improvements, and making the Arrow crate safe by default.