IndexedDB - Performance Comparisons: Part 1

See IndexedDB Performance Comparisons here

In my previous post, I had written about the IndexedDB performance test cases that I had been working on. With the infrastructure set up, this post talks about some of the findings from the test cases. I plan to add more cases and this is the first part in a series.

Note: This post if NOT about comparing browsers, or comparing one storage technology against another. Instead, the focus here is to pick out common IndexedDB patterns and see how a developer may have to change their code for best performance. Each of the test case has a comments section to discuss the outcome.

General Tests
The first set of tests are about performance of comparisons based on the type of  keys. The results are as expected with integers and longs being the fastest and arrays being the slowest. Note that nested arrays are even worse.
Opening database with and without a version seems to be almost the same - except in Firefox where specifying a version make is around 10% faster. This could due to the extra time taken for looking up the table meta data stored in a different table? 
Similarly, the different in a write operation due to the presence (or absence) of keypaths and auto-increments are not very pronounced.

Transactions and batching up read/write requests
In theory, read transactions can occur in parallel, while write transactions wait for other write transactions to finish. The tests however seem to tell a different story. If every read request is placed in its own transaction, it is much slower than queuing the requests. Looks like the time taken to create a transaction out-weighs the time take for a request to be queued and executed. The results for writing data as as expected. Note that grouping read transactions is probably a better way, instead of queuing all reads in a single transaction.

Object Stores and Transactions.
Does including multiple object stores in a transaction scope change things? The time taken to create a transaction becomes greater with the number of stores in the transaction's scope. Also, read operations in transactions with a scope of lesser object store is faster.It is even more pronounced in write transactions where the contention for stores increases when more stores are included in the transaction scope.

This is just the first part in the series of IndexedDB analysis. Watch out this space for more tests, and more results. To make the tests statistically significant, please run the tests located at Also add your comments to the end of each test, pointing out any significant surprises you might encounter.