QuestDB uses a column-based storage model. Data is stored in tables with each column stored in its own file and its own native format. New data is appended to the bottom of each column to allow data to be organically retrieved in the same order versus ingestion.
QuestDB appends one column at a time and each one is updated using the same method. The tail of column file is mapped into the memory page in RAM and the column append is effectively a memory write at an address. Once the memory page is exhausted it is unmapped (thus writing data to disk) and the new page is mapped at a new append offset.
This method ensures minimum resource churn and consistent append latency.
Table columns are randomly accessible. Columns with fixed size data types are read by translating the record number into a file offset by a simple bit shift. The offset in the column file is then translated into an offset in a lazily mapped memory page, where the required value is read from.
QuestDB utilizes ACID properties (Atomicity, Consistency, Isolation, Durability) to ensure data integrity during a transaction. QuestDB’s transaction size is only limited by the available disk space.
To guarantee atomicity, each table maintains a
last_committed_record_count in a separate file.
By convention, any table reader will never read more records than
This enables the property
isolation: where uncommitted data cannot be read.
Since uncommitted data is appended directly to the table,
Once all data is appended, QuestDB
commit() ensures that the
tx_count is updated atomically both in multi-threaded and multi-process environments.
It does so
lock-free to ensure minimal impact on concurrent reads.
The consistency assurance of the data stored is limited to QuestDB auto-repairing abnormally terminated transactions. We do not yet support user-defined constraints, checks and triggers.
Data durability can be configured with commit() optionally being able to invoke msync() with a choice of synchronous or asynchronous IO.
The QuestDB storage model uses memory mapped files and cross-process atomic transaction updates as a low overhead method of inter-process communication. Data committed by one process can be instantaneously read by another process either randomly (via queries) or incrementally (as data queue). QuestDB provides a variety of reader implementations.