A couple of weeks passed after our big 2.0 launch, but we didn’t stop adding cool new features to Memgraph. For this release, we focused on providing you with more options for ingesting your data into Memgraph, and we also enhanced the existing methods. Moreover, we enriched the details of using Memgraph itself, making it simpler than ever to work with.
On Wednesday, December 1st, we will be holding a live demo for the new Memgraph release. If you don’t want to wait for the live stream, check out this video by our CTO Marko 👇
Even though Kafka is by far the most popular option for a streaming platform, it’s not the only one. The streaming world is a growing field with a couple of interesting solutions to your streaming problems.
First comes Pulsar. We added native support inside Memgraph for connecting to your Pulsar cluster. Process the messages in the same way as you can with Kafka, by defining a transformation procedure and running a couple of queries. Try it out using our example, and don’t forget to check the reference guide.
By supporting Kafka, we had to check Redpanda, which claims to be a Kafka API compatible streaming platform. Luckily, that statement is 100% true, allowing you to connect your Redpanda cluster using our Kafka client. If you think your Kafka cluster is slow, try Redpanda with Memgraph and tell us what you think.
We added a new built-in procedure called
mg.kafka_set_stream_offset that allows you to set the offset for the topics of your Kafka connection. No need to use external tools when you can do it straight from Memgraph.
When your messages are processed, they generate queries that are run as part of a transaction. If that transaction was in conflict with another transaction, the processing would fail and stop. Those situations can be annoying, so we decided to retry those transactions automatically a set amount of times. You can control the number of retries and the interval of the retries yourself using newly added configs,
One of the biggest things missing while using Memgraph is any kind of feedback when a query is executed successfully. We added two things to the query summary to solve that problem:
Currently, you can extract that information manually from the summary, but this allows us to improve our CLI tool, mgconsole, and Memgraph Lab.
There are some smaller things we fixed and introduced into Memgraph, which include the following:
BOOTSTRAP_SERVERSas config in
CREATE KAFKA STREAMquery
For more details, check out our Change Log.
If you spot any bugs or generally weird behavior, please drop us a line on our issues page and forum. And remember, if you need any kind of information about Memgraph, the documentation site will always be by your side.
We also invite you to join our Discord Server and stay informed on everything Memgraph related!
Over the course of ten weeks, we had four interns join Memgraph. They worked directly on the Memgraph product.
Learn how to connect to a Pulsar cluster, create an Art Blocks NFT database in Memgraph and analyze streaming sales