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If you're considering Kafka, also check Pulsar (https://pulsar.apache.org/ https://pulsar.apache.org/). Also the dashboard: https://github.com/apache/pulsar-man

If you're considering Kafka, also check Pulsar (https://pulsar.apache.org/ https://pulsar.apache.org/). Also the dashboard: https://github.com/apache/pulsar-manager https://github.com/apache/pulsar-manager

arnon 7y ago
Why should I consider Pulsar instead of Kafka?
- manigandham 7y ago
  Separates storage from brokers for better scaling and performance. Millions of topics without a problem and built-in tenant/namespace/topic hierarchy. Kubernetes-native. Per-message acknowledgement instead of just an offset. Ephemeral pub/sub or persistent data. Built-in functions/lambda platform. Long-term/tiered storage into S3/object storage. Geo-replication across clusters.
  - philote 7y ago
    I'd looked into Kafka before and really liked the partitioned topics and specifying partition keys. This makes sure only one consumer handles all messages for a specific key. Is there a way to do this in Pulsar? I see they have partitioned topics but it seems to only for performance reasons, but I don't see how you'd set up a partition key or make sure a specific key would always go to the same consumer. EDIT: Also wanted to note that, for Python, there is some support for async clients in Kafka (aiokafka, asynckafka) but I don't see any async libs for Pulsar yet. Maybe I'm missing something.
    - manigandham 7y ago
      Yes, you can tag messages with a 'key' for compaction (maintaining the latest message for a given key) and there's now a beta feature for key-ordered consumers on the same topic: https://pulsar.apache.org/docs/en/concepts-messaging/#key_shared https://pulsar.apache.org/docs/en/concepts-messaging/#key_sh... You can also just use separate topics since they're very lightweight and can be nested under the tenant/namespace hierarchy.
  - staticassertion 7y ago
    Wow, yeah that does sound way better than Kafka, and very useful for what I'm doing. Thanks.
- tiew9Vii 7y ago
  It has all the bits missing from Kafka you want and they are trying to bolt on to Kafka. Tiered storage Geo replication Multi-tenancy Massive partition counts Benchmarks have lower latency Really the question should be why Kafka over Pulsar and the only real answer is it’s been around longer and Confluent are really aggressive with their marketing, as an example you might often hear “why Kafka is more ACID than your database” from Confluent, or “Kafka does exactly once” vs effectively once with idempotent operations.
bsaul 7y ago
Just looked at the github page, and i’m surprised by the small number of contributors (for a project that’s been in production in a big company for years). I find it even more worrying knowing that this project has a lot of very advanced features that look like they’d require a lot of people to maintain...
- rad_gruchalski 7y ago
  Don’t judge the book by the cover. Pulsar is built on top of another Apache project: BookKeeper. You can use BookKeeper directly.
  - bsaul 7y ago
    Ha, indeed that's an interesting thing to known and it explains the situation way better. I think they should emphasize that in the pulsar documentation (i read "BookKeeper" in their doc but didn't figure out that it was another independant apache project).
jgraettinger1 7y ago
If this is the plugging subthread: gazette is another project in this space which plays particularly well with batch workflows (https://gazette.dev https://gazette.dev). It’s streaming consumer framework is Go only today, however.
- ryanworl 7y ago
  It is interesting that you made the decision to commit to all replicas of a journal before acknowledging a write and rely on etcd for explicit failure monitoring and re-configuration. FoundationDB also does this, relying on an internal metadata store called the "coordinators", which store some small configuration state. Have you ever found the 20s failure detection window to be too long? FoundationDB's failure monitor pings hosts approximately once a second, so failures are detected very quickly. If you were willing to dedicate a process in the cluster to failure monitoring, you might be able to shrink that window.
  - jgraettinger1 7y ago
    What you describe is how Etcd leases work, just inverted: clients instead check in with the Etcd leader at prescribed intervals or face lease revocation. The leader is doing some add'l clever things like scaling check-in intervals to not DoS itself. 20s is configurable per-client, and gazette lifts this default from etcd. This one number is trying to summarize the tension and trade-off inherent in the (famously hard) problem of distributed failure detection. Network flakes or partitions of a few seconds are all too common and you don't necessarily want to assume failure if one occurs (particularly given the compounding effects of resend timers, etc). In practice, no, it's not been a problem since clients typically buffer writes anyway, in order to batch many small writes into few larger ones.
    - ryanworl 7y ago
      I didn’t mean to imply they were different approaches (they aren’t really), only that you could offload the job from etcd to somewhere else to rely on it less, which would hopefully help scalability or allow you to lower the ping time. And yes, FDB separates the act of detecting a failure from reacting to a detected failure for that reason. In FDB’s case, a 20s network hiccup on a specific process could mean it is better to initiate a recovery anyway. I think for your use case that trade off makes sense as there are lots of journals, whereas FDB only runs a single database for clients to access.
SEJeff 7y ago
How does it compare to Liftbridge, besides being a lot heavier weight? https://github.com/liftbridge-io/liftbridge https://github.com/liftbridge-io/liftbridge https://liftbridge.io/ https://liftbridge.io/
- rad_gruchalski 7y ago
  In Pulsar, storage can be added at runtime. Storage is decoupled from ingest. That’s what makes Pulsar unique.
  - SEJeff 7y ago
    That is a really neat operational benefit. Thanks!
  - jgraettinger1 7y ago
    To be fair, there's a bunch of prior art here: hasn't FB's Scribe has been doing this since 2008, for example?

arnon 7y ago

Why should I consider Pulsar instead of Kafka?

manigandham 7y ago
Separates storage from brokers for better scaling and performance. Millions of topics without a problem and built-in tenant/namespace/topic hierarchy. Kubernetes-native. Per-message acknowledgement instead of just an offset. Ephemeral pub/sub or persistent data. Built-in functions/lambda platform. Long-term/tiered storage into S3/object storage. Geo-replication across clusters.
- philote 7y ago
  I'd looked into Kafka before and really liked the partitioned topics and specifying partition keys. This makes sure only one consumer handles all messages for a specific key. Is there a way to do this in Pulsar? I see they have partitioned topics but it seems to only for performance reasons, but I don't see how you'd set up a partition key or make sure a specific key would always go to the same consumer. EDIT: Also wanted to note that, for Python, there is some support for async clients in Kafka (aiokafka, asynckafka) but I don't see any async libs for Pulsar yet. Maybe I'm missing something.
  - manigandham 7y ago
    Yes, you can tag messages with a 'key' for compaction (maintaining the latest message for a given key) and there's now a beta feature for key-ordered consumers on the same topic: https://pulsar.apache.org/docs/en/concepts-messaging/#key_shared https://pulsar.apache.org/docs/en/concepts-messaging/#key_sh... You can also just use separate topics since they're very lightweight and can be nested under the tenant/namespace hierarchy.
- staticassertion 7y ago
  Wow, yeah that does sound way better than Kafka, and very useful for what I'm doing. Thanks.
tiew9Vii 7y ago
It has all the bits missing from Kafka you want and they are trying to bolt on to Kafka. Tiered storage Geo replication Multi-tenancy Massive partition counts Benchmarks have lower latency Really the question should be why Kafka over Pulsar and the only real answer is it’s been around longer and Confluent are really aggressive with their marketing, as an example you might often hear “why Kafka is more ACID than your database” from Confluent, or “Kafka does exactly once” vs effectively once with idempotent operations.

bsaul 7y ago

Just looked at the github page, and i’m surprised by the small number of contributors (for a project that’s been in production in a big company for years). I find it even more worrying knowing that this project has a lot of very advanced features that look like they’d require a lot of people to maintain...

rad_gruchalski 7y ago
Don’t judge the book by the cover. Pulsar is built on top of another Apache project: BookKeeper. You can use BookKeeper directly.
- bsaul 7y ago
  Ha, indeed that's an interesting thing to known and it explains the situation way better. I think they should emphasize that in the pulsar documentation (i read "BookKeeper" in their doc but didn't figure out that it was another independant apache project).

jgraettinger1 7y ago

If this is the plugging subthread: gazette is another project in this space which plays particularly well with batch workflows (https://gazette.dev https://gazette.dev). It’s streaming consumer framework is Go only today, however.

ryanworl 7y ago
It is interesting that you made the decision to commit to all replicas of a journal before acknowledging a write and rely on etcd for explicit failure monitoring and re-configuration. FoundationDB also does this, relying on an internal metadata store called the "coordinators", which store some small configuration state. Have you ever found the 20s failure detection window to be too long? FoundationDB's failure monitor pings hosts approximately once a second, so failures are detected very quickly. If you were willing to dedicate a process in the cluster to failure monitoring, you might be able to shrink that window.
- jgraettinger1 7y ago
  What you describe is how Etcd leases work, just inverted: clients instead check in with the Etcd leader at prescribed intervals or face lease revocation. The leader is doing some add'l clever things like scaling check-in intervals to not DoS itself. 20s is configurable per-client, and gazette lifts this default from etcd. This one number is trying to summarize the tension and trade-off inherent in the (famously hard) problem of distributed failure detection. Network flakes or partitions of a few seconds are all too common and you don't necessarily want to assume failure if one occurs (particularly given the compounding effects of resend timers, etc). In practice, no, it's not been a problem since clients typically buffer writes anyway, in order to batch many small writes into few larger ones.
  - ryanworl 7y ago
    I didn’t mean to imply they were different approaches (they aren’t really), only that you could offload the job from etcd to somewhere else to rely on it less, which would hopefully help scalability or allow you to lower the ping time. And yes, FDB separates the act of detecting a failure from reacting to a detected failure for that reason. In FDB’s case, a 20s network hiccup on a specific process could mean it is better to initiate a recovery anyway. I think for your use case that trade off makes sense as there are lots of journals, whereas FDB only runs a single database for clients to access.

SEJeff 7y ago

How does it compare to Liftbridge, besides being a lot heavier weight? https://github.com/liftbridge-io/liftbridge https://github.com/liftbridge-io/liftbridge https://liftbridge.io/ https://liftbridge.io/

rad_gruchalski 7y ago
In Pulsar, storage can be added at runtime. Storage is decoupled from ingest. That’s what makes Pulsar unique.
- SEJeff 7y ago
  That is a really neat operational benefit. Thanks!
- jgraettinger1 7y ago
  To be fair, there's a bunch of prior art here: hasn't FB's Scribe has been doing this since 2008, for example?