🚀 Timeplus Enterprise v2.8 | Iceberg Integration, Auto-Scaling Materialized Views, S3 Tiered Storage, and more
Hear Timeplus Enterprise updates from our team and use cases from our customers! See the latest recording of our Timeplus Live monthly webinar, How ServiceRadar Builds Distributed Network Monitoring Systems with Timeplus, featuring special guest and our community user Michael Freeman.
Timeplus Enterprise v2.8 is now Generally Available! Read on to learn about the key advancements in this release:
🧊 Integration with Apache Iceberg
⚖️ Elastic Materialized Views with auto-scaling compute nodes
🗄️ S3 tiered storage, optimizing data retention
📝 New SQL command to rename streams or columns
⚙️ JavaScript UDFs now benefit from multiple V8 instances
🔵 New monitoring page to visualize nodes in a cluster
👀 New details pages for streams or Materialized Views
... and more
Timeplus Enterprise v2.8.1 is the current stable build (Public GA) 🛠️
🤩 Customer Spotlight
In a recent case study, we explored how a leading cryptocurrency data platform leveraged Timeplus Enterprise to streamline fragmented tooling, reduce analytics latency, and improve cost efficiency. While the use case centers on blockchain data, the lessons learned apply broadly to industries dealing with high-cardinality, mutable data and real-time analytics demands. Mathew Haji, founder at Zyre , says:
“We tried countless tools and rewrote our pipeline multiple times. Timeplus was the first solution that let us index the full Ethereum chain—and now, any chain—in real-time. It’s transformed how we deliver data to our customers.”
To learn more about Zyre's use case, check out our case study.
🧊 Read/Write in Apache Iceberg Open Table Format
Timeplus is one of the first vendors to integrate with Apache Iceberg purely in C++. In this release, we've added native support for Iceberg as a new database type, so you can read and write data in the open table format, including support for the Iceberg REST Catalog (IRC).
Stream to Storage: Use Materialized Views to transform streaming data and write to Apache Iceberg
No Lock-In: Iceberg’s open table format works with multiple engines
Future-Proof: Backed by broad industry support and a strong open-source community
See it in action! Check out our Apache Iceberg Integration demo.
⚖️ Auto-Scaling Materialized Views
Introducing Compute Nodes, a new type of server node that leverages AWS Spot Instances or Auto Scaling Group. This allows Timeplus clusters to dynamically add or remove nodes to schedule the Materialized Views on-demand, in response to changing workloads.
Our Chief Architect, Ken Chen, shares a demo here:
🗄️ S3 Tiered Storage
Tiered Storage allows users to combine local and remote storage, storing hot data in local high-performance storage (like NVMe SSD) for quick access, and moving older data to object storage (like S3) for long-term retention. This helps you greatly reduce storage costs when dealing with massive amounts of data.
In the example below, the most recent seven days of data are stored on Timeplus cluster disks, while older data is automatically moved to the S3 bucket.
✨ Other Enhancements
Direct read and write access to PostgreSQL External Table, or data lookup via dictionaries, through PostgreSQL External Table
New SQL command to rename streams or columns
JavaScript UDFs benefit from multiple V8 instances, improving concurrency and isolation
Clean up cache when updating Protobuf schemas
New monitoring page to visualize nodes in a cluster
New details pages for streams or Materialized Views
⚙️ What's New In Timeplus Proton
v1.6.12, v1.6.14, and v1.6.15
Support AWS_MSK_IAM authentication for accessing Amazon MSK
Allowing tuple datatype for the 1st param of array_map
New function group_array_last
Support format schema for Avro
Fixed bug where meta store raft service is hardcoded to listen on ipv6
For more details about our latest releases, please see release notes in our docs.
👀 More Resources from Timeplus
v2.8 Announcement: Learn more about new features in Timeplus Enterprise v2.8 in this announcement blog by our Head of Product Jove Zhong. Read Blog
May Timeplus Live Webinar Recap: See our May Timeplus Live webinar recording, "How ServiceRadar Builds Distributed Network Monitoring Systems with Timeplus", with special guest Michael Freeman. Watch Webinar Recording
Demo Video: See how to capture CDC data from a MySQL database via Debezium and Kafka, transform data, and store it in Google Cloud Storage (GCS). Watch Demo
Demo Video: See a demo of our new AI-powered data onboarding process. Integrate with your Apache Kafka, then leverage AI to generate a CREATE DDL and SQL analysis recommendations. Watch Demo
Blog Post: Our CTO Gang Tao shares how to build a real-time GPU monitoring system using Timeplus, NVIDIA's DCGM-Exporter, Vector, and Redpanda. Read Blog
Blog Post: Gang Tao demonstrates how you can build a real-time video stream analytic tool with Timeplus and Roboflow's computer vision capabilities. Read Blog
🛠️ Ready to start building?
🗄️ Self-Hosted Timeplus Enterprise v2.8.1 is the current stable build (Public GA). See installation options and download a 30-day free trial.
🔍 See Timeplus in action: Explore our demo workspace with live data.
⭐ Visit Proton GitHub repo: github.com/timeplus-io/proton
📬 Have questions or comments for us? Get in touch to discuss your unique use cases.
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