IginX v0.5.0 -- Embarking to lead and to embrace!

The download link for the All-in-One Fast-Deploy binary package IginX-FastDeploy-v0.5.0-bin.zip
The download link for the IginX-Release-Only binary package IginX-release-v0.5.0-bin.zip

• Change IginX query language to be compatible with standard SQL
• Add TagKV support
• Add preliminary sub-queries
• Add Python UDF engine
• Add Python processing flow engine
• Add annotation support on time series segments
• Add API for curve matching
• Introduce a pluggable query optimizer on the operator tree
• Introduce a pluggable validator on the logical plan
• Introduce a pluggable execution optimizer on the tree of execution tasks
• Add session APIs to be compatible with InfluxDB
• Add tests on new SQL statements and functionalities
• Add storage interface for PostgreSQL database
• Add storage interface for TimescaleDB database
• Add storage interface for OpenTSDB database
• Add HistoricalPolicy for importing time-irrelevant historical data imports

IginX v0.4.0 -- Serving You Online

• Adding new policies for realistic Online serving
• Adding aggregations along both series dimension and time dimension
• Working with Python and Go clients
• Rejecting on overloading requests
• Fixing some bugs...

IginX v0.3.0 - Beginning to be capable of breaking the TPCx-IoT world record

• A command client for SQL-like interactions.
• The JDBC support.
• Multi-version DB instance runtime support.
• MQTT support.
• A workload-aware load balancing policy.
• Two more choices for metadata management, i.e., etcd and file storage.
• Fully support TPCx-IoT tests.
• Docker deployment support.
• Basic authorization management.
• Fix metadata management for scaling process.

IginX v0.2.0

• Fully support API functions of IoTDB
• Equivalent support on InfluxDB
• RESTful service similar to IKR
• Extra RESTful service on:
  • Annotations
  • Grafana Interfaces
• Fix bugs

The debut of IginX

This release supports only time series ingestion, time range-based reads, and simple aggregations. However, this release has some features that are favorable to users:

• High Scalability
• Smooth Elasticity
• Transparent Data Distribution
• Integration with Heterogeneous Databases
• Flexible Slicing and Replication