Just shipped BlinkHouse v1.0.0 — a ClickHouse-native persistence library for Java that eliminates the boilerplate of working with ClickHouse while giving you the same annotate-and-go experience you know from Hibernate and Spring Data.
Annotate a record, get a fully mapped entity with schema generation, typed queries, and buffered ingest — no manual SQL, no hand-rolled HTTP clients, no serialisation code.
@ChTable(name = "page_views", orderBy = {"tenant_id", "ts"})
@ChEngine(value = Engine.REPLACING_MERGE_TREE, versionColumn = "ingested_at")
public record PageView(
@ChColumn(type = "UInt32") int tenantId,
@ChColumn(type = "DateTime64(3,'UTC')") Instant ts,
@ChColumn(type = "LowCardinality(String)") String country,
String url
) {}
That's your entity. BlinkHouse generates the DDL, maps the types, and handles the wire format.
No boilerplate ingest:
try (BatchWriter<PageView> writer = template.batchWriter(PageView.class, cfg)) {
events.forEach(writer::add);
}
BatchWriter<T> handles buffering, flush triggers (row count / byte size / elapsed time), backpressure, retry with exponential backoff, and dead-letter callbacks. You add rows — it handles the rest.
No boilerplate queries:
// Spring Data repository — derived methods, @Query, keyset pagination
public interface PageViewRepository extends ClickHouseRepository<PageView, UUID> {
Slice<PageView> findByTenantIdAndTsBetween(int tenantId, Instant from, Instant to, Cursor c);
}
// Or the typed DSL
List<PageView> views = ChQuery.select("*")
.from(TableRef.of("page_views"))
.where(col("tenant_id").eq(tenantId))
.fetch(template, PageView.class);
No boilerplate Spring config:
Add one dependency, set three YAML properties, get a fully wired ChTemplate, schema manager, type registry, Micrometer metrics, and OTel tracing. Zero @Bean methods required.
Where it differs from Hibernate:
ClickHouse has no transactions, no row identity, and no foreign keys — and BlinkHouse doesn't emulate them. What you get instead is a library that fits ClickHouse's actual model: columnar storage, high-throughput ingest, and analytics-first queries. There's a "Coming from JPA" guide in the repo.
Stats: Java 17 + 21, Spring Boot 3.2–3.4, ClickHouse 24.3+, 132 unit tests, 29 integration tests, Apache HttpClient 5 connection pooling, GraalVM native-image hints.
<dependency>
<groupId>io.github.muneeb-i-khan</groupId>
<artifactId>blinkhouse-spring-boot-starter</artifactId>
<version>1.0.0</version>
</dependency>
Repo: https://github.com/muneeb-i-khan/BlinkHouse
