ES 6 • ES 7 • ES 8 • ES 9 — One SQL Interface

Stop ETL’ing Elasticsearch into your warehouse just to JOIN it.

Single-cluster or cross-cluster JOINs on Elasticsearch — via JDBC, ADBC, or Arrow Flight SQL. Pick your scale.

Free in Community Single-cluster: drop in our driver Cross-index JOINs across your existing ES indices — JDBC, ADBC, or Arrow Flight SQL. No ETL. JDBC quickstart → Pro+ Multi-cluster federation: deploy our server JOIN across regional ES clusters from one SQL query — available now (Pro+). Helm-driven topology, forward-compatible with heterogeneous sources in the upcoming release (Quarter 1 2027). Federation operator guide →

Terminal

curl -fsSL https://raw.githubusercontent.com/SOFTNETWORK-APP/SoftClient4ES/main/install.sh | bash
softclient4es --host localhost --port 9200

Apache 2.0 ES 6 – 9 Scala 2.12 / 2.13 Arrow Flight SQL

Works with

Apache Superset DBeaver Grafana DataGrip Tableau DuckDB

SRE & Platform

Correlate logs, metrics, and traces across regional ES clusters in a single SQL query.

One incident, several regions, several clusters. Instead of pivoting across N dashboards, JOIN the per-region indices in one query and read the timeline straight across.

Cross-cluster correlation runs on the federation server (Pro+). See the editions & pricing, then the federation operator guide.

Cross-region incident triage Federation (illustrative)

-- Illustrative: substitute your own per-region index names.
-- Catalog prefixes route each leg to its regional cluster.
SELECT u.user_id, u.action, e.error_code, e.region
FROM `prod_us`.user_events u
JOIN `prod_eu`.error_events e
  ON u.user_id = e.user_id
WHERE e.ts > NOW() - INTERVAL '15' MINUTE
ORDER BY e.ts;

Measured

From Elasticsearch to DuckDB, parsed once

Every stack pays the same Elasticsearch serialization step on the way out of the cluster: every format its search and SQL endpoints offer is a row-serialized document encoding. SoftClient4ES converts to Apache Arrow once, at the sidecar — and those exact columnar buffers are what land in DuckDB, pandas, or Polars. Zero re-serialization after the sidecar.

It moves what it must, not what it can

A GROUP BY returning 100 rows compiles into an Elasticsearch aggregation: 0.043 s, and 27.1 KB leaves the cluster. Trino’s Elasticsearch connector performs predicate push-down only, per its documentation, so it scans all ten million rows out of the cluster first — 5.50 s, and 1.39 GB of egress.

It costs the client far less

Landing all ten million rows as a columnar table costs 2.83 s of client CPU against 24.05 s for Trino’s documented client, and fits in a 2 GB container where that client is OOM-killed even with 8 GB. In an 8 GB budget it completes five concurrent extractions where the documented client completes none and Trino’s fastest completes two.

And it is faster

11.91 s against 14.66 s for Trino’s fastest client and 44.70 s for its documented one — a factor of 1.23 to 3.75 depending on the route. The low end is the serious comparison: nobody extracts ten million rows through the documented client on purpose.

Where Trino is stronger: its fastest client uses less client memory than we do — 617 MB against our 921 MB. Elasticsearch’s own ES|QL pushes the same aggregation down and ties us on that cell.

Terminal demo: the same ten-million-row SELECT run one stack after the other — first Trino's JSON client protocol, then Arrow Flight SQL into DuckDB — followed by the push-down comparison. — “SoftClient4ES keeps the wall-clock lead against every Trino client — 1.23× against the fastest of them, 3.75× against the documented one.”
Measured 2026-08-21 · Elasticsearch 8.18.3 · Trino 483 · sidecar 0.3.0 — scenes show one live run each; the quoted claim is the session median.

Methodology, full results, and where Trino is stronger Read the wire-format deep dive →

SQL for Every Role

One suite, three perspectives — each team finds what they need.

Data Engineers

Build Pipelines, Not JSON

Ingest, transform, and materialize data across Elasticsearch indices using standard SQL — no custom scripts, no REST API gymnastics.

DML — INSERT, UPDATE, DELETE with SQL expressions
COPY INTO — bulk load from S3, local files (JSON, CSV, Parquet)
Cross-index JOIN — JOIN across ES indices in one query; ES can’t do this natively
Materialized Views — persist a pre-joined, pre-aggregated index
Arrow Flight SQL — Arrow-native, zero-copy columnar streaming — measured on ten million rows

Data Pipeline in SQL COPY INTO + MV

-- Ingest from S3
COPY INTO raw_events
FROM 's3://lake/events.parquet'
FORMAT PARQUET;

-- Materialize a cross-index JOIN
CREATE MATERIALIZED VIEW
  order_details AS
SELECT o.id, c.name, SUM(o.amount)
FROM orders o
JOIN customers c
  ON o.customer_id = c.id
GROUP BY o.id, c.name;

Data Analysts

Connect Your BI Tools

Query Elasticsearch with the SQL you already know. Connect Superset, Grafana, Tableau, or DBeaver — no Elasticsearch expertise required.

JDBC Type 4 — plug into any JDBC-compatible BI tool
Window functions — AVG OVER, FIRST_VALUE, ARRAY_AGG
Multi-nested queries — navigate complex ES mappings naturally
Materialized Views — query persisted, pre-joined data instantly (one of two ES-impossible superpowers, alongside query-time cross-index JOIN)
ADBC — DuckDB, pandas and Polars via the standard Flight SQL driver

Analytics Query Window Functions

SELECT name, department, salary,
  AVG(salary) OVER (
    PARTITION BY department
  ) AS dept_avg,
  FIRST_VALUE(name) OVER (
    PARTITION BY department
    ORDER BY salary DESC
  ) AS top_earner
FROM employees
WHERE hire_date > '2024-01-01';

Platform / DevOps

Manage Schemas with SQL

CREATE, ALTER, DROP indices with familiar DDL. One unified API across ES 6 through 9 — no version-specific JSON mappings.

DDL — CREATE TABLE, ALTER TABLE, DROP TABLE
GatewayApi — one interface for ES 6, 7, 8, and 9
Interactive REPL — explore, debug, and manage from the terminal
No ES license required — Apache 2.0 core, external client

Schema Management DDL

CREATE TABLE users (
  id KEYWORD,
  name TEXT,
  email KEYWORD,
  age INTEGER,
  created_at DATE,
  PRIMARY KEY (id)
);

ALTER TABLE users
  ADD COLUMN status KEYWORD;

-- Explore from the REPL
SHOW TABLES;
DESCRIBE users;

NLPchina:No

Trino ES:No

OpenSearch:No

JDBC Driver

SoftClient4ES: Type 4

Elastic SQL:Paid

CData:Yes

NLPchina:No

Trino ES:Via Trino

OpenSearch:Yes

Arrow Flight SQL

SoftClient4ES: Yes

Elastic SQL:No

CData:No

NLPchina:No

Trino ES:Via Trino

OpenSearch:No

ADBC Driver

SoftClient4ES: Yes

Exclusive

Elastic SQL:No

CData:No

NLPchina:No

Trino ES:No

OpenSearch:No

Licensing: SoftClient4ES core is Apache 2.0. Extensions (Materialized Views, JDBC, ADBC, Arrow Flight SQL) are Elastic v2 license.

Explore all features in detail →

Ready to JOIN your Elasticsearch indices?

Drop in a driver, run a cross-index JOIN in minutes — free in Community. No ETL, no warehouse.

JDBC Quickstart View on GitHub