1 point by datajunkie 1 year ago flag hide 21 comments
dataengineer123 1 year ago next
Great question! PostgreSQL is a powerful database, and optimizing it for real-time data streaming involves several steps. Here are some pointers:
dbaexpert007 1 year ago next
First, consider using a data schema design that fits your use case. Real-time data streaming typically requires a denormalized data schema with minimal joins. Consider using a star or snowflake schema.
etlwizard 1 year ago next
If the data volume is high, you might consider using a columnar database like CStore_FDW or Citus Data to horizontally scalable PostgreSQL. That can handle real-time data streaming workloads more efficiently.
postgresholic 1 year ago prev next
For the database tuning, you'll want to look at increasing shared buffers and dedicated unix-domain socket for connections. Also, setting up work-mem and effective_cache_size can help too.
pgfan 1 year ago next
Replication is also important. Use a master-slave or master-master setup for redundancy and read load distribution. You also get a warm standby for failover.
justasking 1 year ago prev next
What about using an ETL tool or Change Data Capture (CDC) for real-time data streaming rather than modifying the database itself?
etlguru 1 year ago next
Using a CDC tool or a real-time ETL tool to stream data into PostgreSQL can offer many benefits. It's a more maintainable and scalable solution than custom database scripts. Additionally, these tools can offer features like automatic schema evolution, error handling, and retries.
technium 1 year ago next
Thanks, @ETLguru. If we choose to go with an ETL tool, what's a reliable, cost-effective tool that you would recommend for real-time data streaming?
etl_allstar 1 year ago next
I'd recommend taking a look at tools like Apache Kafka, Apache Spark, Apache Nifi, and Fivetran. These support real-time data streaming at various scales and offer enterprise-grade features for different use cases.
codemaster01 1 year ago next
@ETL_allstar, are there any open-source tools worth checking out in that list?
etl_allstar 1 year ago next
@codemaster01, Apache Kafka and Apache Spark are open-source. They are quite popular and widely used options, and they offer many features for real-time data streaming.
happycoder 1 year ago prev next
How do you handle indexing?
pgmaster 1 year ago next
Indexing is critical for real-time data streaming as it impacts both read and write performance. Generally, use fewer indexes to scale. Try the most selective indexes first and utilize partial indexes when possible.
datajedi 1 year ago next
@pgmaster, what are partial indexes and why would I use them?
pgmaster 1 year ago next
@datajedi, partial indexes are indexes that only include a subset of rows that meet specific criteria. They're useful in scenarios where only a tiny fraction of rows should match the query, e.g., time-series data streaming.
stackhead 1 year ago prev next
What about partitioning and how it affects the performance of postgreSQL?
database_genius 1 year ago next
Partitioning allows you to divide your large table into smaller, more manageable parts. It enables parallel processing of query results, leading to lower response times. Range partitioning, list partitioning and hash partitioning are popular ways to implement partitioning in PostgreSQL.
scalabilityking 1 year ago next
@database_genius, if I partition my database, will it impact the existing queries?
database_genius 1 year ago next
@scalabilityking, yes, partitioning does affect existing queries if you don't account for the partitioned scheme. Use table and constraint exclusion techniques to ensure your queries consider the partitioned scheme.
bigdatadude 1 year ago prev next
How much of an impact does data types have on real-time data streaming? Surely JSON columns and text overkill for data streaming applications?
dataoptimizationspecialist 1 year ago next
@bigdatadude, data types can impact performance significantly. Using a binary JSON format (JSONB) over plain text JSON columns can offer better ingestion, compression, and querying performance. In PostgreSQL, JSONB provides indexing, querying, and validation benefits.