chore: update the roadmap (#584)

* chore: update the roadmap

* fix: 1.0.0-alpha is released and 1.0 is still in progress

* chore: fix typos and revise works should be done afterwards

* chore: improve some expressions

docs/guides/src/dev/roadmap.md

@@ -14,18 +14,30 @@
 - [x] Static cluster mode with `CeresMeta`.
 - [x] Basic implementation of hybrid storage format.
 
-### v0.4.0 (Released)
+### v0.4.0
 - [x] Implement more sophisticated cluster solution that enhances reliability and scalability of CeresDB.
 - [x] Set up nightly benchmark with TSBS.
 
-### v1.0.0-alpha
-- [ ] Implement Distributed WAL based on `Apache Kafka`.
-- [ ] Release Golang client.
-- [ ] Improve the query performance for traditional time series workloads.
-- [ ] Support dynamic migration of tables in cluster mode.
+### v1.0.0-alpha (Released)
+- [x] Implement Distributed WAL based on `Apache Kafka`.
+- [x] Release Golang client.
+- [x] Improve the query performance for traditional time series workloads.
+- [x] Support dynamic migration of tables in cluster mode.
 
-### Afterward
-- [ ] Support Prometheus protocol.
-- [ ] Implement UDF framework which makes CeresDB more extensible.
-- [ ] Support more underlying storages for adaptivity. For example, the underlying storage could be a distributed file system.
-- [ ] Various tools that ease the use of CeresDB. For example, data import and export tools.
+### v1.0.0
+- [ ] Formally release CeresDB and its SDKs with all breaking changes finished.
+- [ ] Finish the majority of work related to `Table Partitioning`.
+- [ ] Various efforts to improve query performance, especially for cloud-native cluster mode. These works includes:
+    - Multi-tier cache.
+    - Introduce various methods to reduce the data fetched from remote storage (improve the accuracy of SST data filtering).
+    - Increase the parallelism while fetching data from remote object-store.
+- [ ] Improve data ingestion performance by introducing resource control over compaction.
+
+### Afterwards
+With an in-depth understanding of the time-series database and its various use cases, the majority of our work will focus on performance, reliability, scalability, ease of use, and collaborations with open-source communities.
+- [ ] Add utilities that support `PromQL`, `InfluxQL`, `OpenTSDB` protocol, and so on.
+- [ ] Provide basic utilities for operation and maintenance. Specifically, the following are included:
+    - Deployment tools that fit well for cloud infrastructures like `Kubernetes`.
+    - Enhance self-observability, especially critical logs and metrics should be supplemented.
+- [ ] Develop various tools that ease the use of CeresDB. For example, data import and export tools.
+- [ ] Explore new storage formats that will improve performance on hybrid workloads (analytical and traditional time-series workloads).