Storing Cloud Data Over Transient Connections

An interesting challenge in many M2M scenarios is that your network connection is often far from good. If you’re trying to collect Engine data from an over-the-road truck going 80 miles an hour across rural Montana it’s a pretty safe bet that you’re going to have places where you have no access to a network. Even in urban areas you have dead spots, plus there’s always the old “driver put a tuna can over the antenna” scenarios to throw a wrench into things. Just because we lose our connection doesn’t mean we should start throwing data onto the floor though. We need a data storage mechanism that’s robust enough to deal with these kind of problems.

What you need is a local data store for the times when you don’t have connectivity and a remote store when you do. Or maybe a local store that does store-and-forward or replication. Yes, you could roll your own data storage service that can do these things, but why would you when there’s a perfectly good, already written solution out there? Again, you should be abstracting your application’s data services so you can focus on the business problems you’re good at. Solve the problems your company is hired to solve – not the grunt work of putting data into storage.

I added a new feature today to the OpenNETCF ORM called Replication (it’s only in the source downloads right now, not the latest release). A Replicator attaches to any DataStore and ties it to any other DataStore. It doesn’t matter what the actual storage is – there’s the beauty of abstraction, it works with any supported stores – it can take data from one store and push it to anther behind the scenes for you. So you can store to a local SQLite data file and have a Replicator push that data off to an Azure table. And it requires no change in your data Insert logic at all. Zero.

Currently Replicators are simplistic in capability. They can only replicate Inserts, and they only do a “Replicate and Delete” meaning that during replication the data is “moved” from the local store to the remote store, but that’s typically all you need and the typical case is all I’m trying to solve in the first pass.

So what does it look like, you ask? Below is an example of a working test that stores locally to a SQL Compact database, and when the network is up, those rows get moved off to a DreamFactory Cloud table. Notice that the only “new” thing you do here is to define the DataStore where the replicated data goes, you define which Entities will get replicated (it’s opt-in or a per-table basis), and you add the Replicator to the source DataStore’s new Replicators collection (lines 11-29). Yes, that means you could even replicate different tables to different target Stores.

public void BasicLocalReplicationTest()
    var source = new SqlCeDataStore("source.sdf");
    if (!source.StoreExists)

    var destination = new DreamFactoryDataStore(

    if (!destination.StoreExists)

    // build a replicator to send data to the destiantion store
    var replicator = new Replicator(destination, ReplicationBehavior.ReplicateAndDelete);

    // replication is opt-in, so tell it what type(s) we want to replicate

    // add the replicator to the source

    // watch an event for when data batches go out
    replicator.DataReplicated += delegate
        // get a count
        Debug.WriteLine(string.Format("Sent {0} rows", replicator.GetCount<TestItem>()));

    var rows = 200;

    // put some data in the source
    for (int i = 0; i < rows; i++)
        var item = new TestItem(string.Format("Item {0}", i));

    int remaining = 0;
    // loop until the source table is empty
        remaining = source.Count<TestItem>();
    } while(remaining > 0);

    // make sure the destination has all rows
    Assert.AreEqual(rows, destination.Count<TestItem>());

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