Java | SchematicHQ

The official Schematic Java library.

Java version requirements:

Core SDK (flag checks, events, webhooks): Java 8+
Datastream / local flag evaluation: Java 11+ (required by the WASM runtime)

Enabling datastream on a JVM older than 11 will throw a DataStreamException with a clear message at Schematic build time, rather than a cryptic UnsupportedClassVersionError at runtime.

Installation and Setup

Add the dependency using your build tool of choice:

Using Gradle in build.gradle:

1 dependencies {
2     implementation 'com.schematichq:schematic-java:0.x.x'
3 }

Using Maven in pom.xml:

1 <dependency>
2     <groupId>com.schematichq</groupId>
3     <artifactId>schematic-java</artifactId>
4     <version>0.x.x</version>
5 </dependency>

Issue an API key for the appropriate environment using the Schematic app.
Using this secret key, initialize a client in your application:

1 import com.schematic.api.Schematic;
2 
3 Schematic schematic = Schematic.builder()
4     .apiKey("YOUR_API_KEY")
5     .build();

Usage

A number of these examples use keys to identify companies and users. Learn more about keys here.

Sending identify events

Create or update users and companies using identify events.

1 import com.fasterxml.jackson.databind.JsonNode;
2 import com.schematic.api.Schematic;
3 import com.schematic.api.core.ObjectMappers;
4 import java.util.HashMap;
5 import java.util.Map;
6 
7 Schematic schematic = Schematic.builder()
8     .apiKey("YOUR_API_KEY")
9     .build();
10 
11 Map<String, String> keys = new HashMap<>();
12 keys.put("email", "wcoyote@acme.net");
13 keys.put("user_id", "your-user-id");
14 
15 EventBodyIdentifyCompany company = EventBodyIdentifyCompany.builder()
16     .name("Acme Widgets, Inc.")
17     .build();
18 
19 Map<String, JsonNode> traits = new HashMap<>();
20 traits.put("city", ObjectMappers.JSON_MAPPER.valueToTree("Atlanta"));
21 traits.put("high_score", ObjectMappers.JSON_MAPPER.valueToTree(25));
22 traits.put("is_active", ObjectMappers.JSON_MAPPER.valueToTree(true));
23 
24 schematic.identify(keys, company, "Wile E. Coyote", traits);

This call is non-blocking and there is no response to check.

Sending track events

Track activity in your application using track events; these events can later be used to produce metrics for targeting.

1 import com.schematic.api.Schematic;
2 import java.util.HashMap;
3 import java.util.Map;
4 
5 Schematic schematic = Schematic.builder()
6     .apiKey("YOUR_API_KEY")
7     .build();
8 
9 Map<String, String> company = new HashMap<>();
10 company.put("id", "your-company-id");
11 
12 Map<String, String> user = new HashMap<>();
13 user.put("user_id", "your-user-id");
14 
15 Map<String, Object> traits = new HashMap<>();
16 
17 schematic.track("some-action", company, user, traits);

This call is non-blocking and there is no response to check.

If you want to record large numbers of the same event at once, or perhaps measure usage in terms of a unit like tokens or memory, you can optionally specify a quantity for your event:

1 schematic.track("some-action", company, user, traits, 10);

Creating and updating companies

Although it is faster to create companies and users via identify events, if you need to handle a response, you can use the companies API to upsert companies. Because you use your own identifiers to identify companies, rather than a Schematic company ID, creating and updating companies are both done via the same upsert operation:

1 import com.fasterxml.jackson.databind.JsonNode;
2 import com.schematic.api.Schematic;
3 import com.schematic.api.core.ObjectMappers;
4 import com.schematic.api.types.UpsertCompanyRequestBody;
5 import java.util.HashMap;
6 import java.util.Map;
7 
8 Schematic schematic = Schematic.builder()
9     .apiKey("YOUR_API_KEY")
10     .build();
11 
12 Map<String, String> keys = new HashMap<>();
13 keys.put("id", "your-company-id");
14 
15 Map<String, JsonNode> traits = new HashMap<>();
16 traits.put("city", ObjectMappers.JSON_MAPPER.valueToTree("Atlanta"));
17 traits.put("high_score", ObjectMappers.JSON_MAPPER.valueToTree(25));
18 traits.put("is_active", ObjectMappers.JSON_MAPPER.valueToTree(true));
19 
20 UpsertCompanyRequestBody request = UpsertCompanyRequestBody.builder()
21     .keys(keys)
22     .name("Acme Widgets, Inc.")
23     .traits(traits)
24     .build();
25 
26 var response = schematic.companies().upsertCompany(request);
27 System.out.println("Company upserted: " + response.getData().getName());

Checking flags

When checking a flag, you’ll provide keys for a company and/or keys for a user. You can also provide no keys at all, in which case you’ll get the default value for the flag.

1 import com.schematic.api.Schematic;
2 import java.util.HashMap;
3 import java.util.Map;
4 
5 Schematic schematic = Schematic.builder()
6     .apiKey("YOUR_API_KEY")
7     .build();
8 
9 Map<String, String> company = new HashMap<>();
10 company.put("id", "your-company-id");
11 
12 Map<String, String> user = new HashMap<>();
13 user.put("user_id", "your-user-id");
14 
15 boolean flagValue = schematic.checkFlag("some-flag-key", company, user);

Webhook Verification

Schematic can send webhooks to notify your application of events. To ensure the security of these webhooks, Schematic signs each request using HMAC-SHA256. The Java SDK provides utility functions to verify these signatures.

Verifying Webhook Signatures

When your application receives a webhook request from Schematic, you should verify its signature to ensure it’s authentic:

1 import com.schematic.webhook.WebhookVerifier;
2 import com.schematic.webhook.WebhookSignatureException;
3 import java.util.Map;
4 import java.util.HashMap;
5 import java.io.BufferedReader;
6 import java.io.IOException;
7 
8 // In your webhook endpoint handler:
9 public void handleWebhook(HttpServletRequest request, HttpServletResponse response) throws IOException {
10     // Read the request body
11     String body = request.getReader().lines().collect(Collectors.joining("\n"));
12 
13     // Get the required headers
14     Map<String, String> headers = new HashMap<>();
15     headers.put(WebhookVerifier.WEBHOOK_SIGNATURE_HEADER,
16                 request.getHeader(WebhookVerifier.WEBHOOK_SIGNATURE_HEADER));
17     headers.put(WebhookVerifier.WEBHOOK_TIMESTAMP_HEADER,
18                 request.getHeader(WebhookVerifier.WEBHOOK_TIMESTAMP_HEADER));
19 
20     String webhookSecret = "your-webhook-secret";
21 
22     try {
23         // Verify the webhook signature
24         WebhookVerifier.verifyWebhookSignature(body, headers, webhookSecret);
25 
26         // Process the webhook payload
27         // ...
28 
29         response.setStatus(HttpServletResponse.SC_OK);
30     } catch (WebhookSignatureException e) {
31         // Handle signature verification failure
32         response.setStatus(HttpServletResponse.SC_UNAUTHORIZED);
33         response.getWriter().write("Invalid signature: " + e.getMessage());
34     }
35 }

Verifying Signatures Manually

If you need to verify a webhook signature outside of the context of a servlet request, you can use the verifySignature method:

1 import com.schematic.webhook.WebhookVerifier;
2 import com.schematic.webhook.WebhookSignatureException;
3 
4 public void verifyWebhookManually(String body, String signature, String timestamp, String secret) {
5     try {
6         WebhookVerifier.verifySignature(body, signature, timestamp, secret);
7         System.out.println("Signature verification successful!");
8     } catch (WebhookSignatureException e) {
9         System.out.println("Signature verification failed: " + e.getMessage());
10     }
11 }

Configuration Options

There are a number of configuration options that can be specified using the builder when instantiating the Schematic client.

Flag Check Options

By default, the client will do some local caching for flag checks. If you would like to change this behavior, you can do so using initialization options to specify the cache providers:

1 import com.schematic.api.Schematic;
2 import com.schematic.api.cache.LocalCache;
3 import java.time.Duration;
4 import java.util.Collections;
5 
6 Schematic schematic = Schematic.builder()
7     .apiKey("YOUR_API_KEY")
8     .cacheProviders(Collections.singletonList(new LocalCache<>()))
9     .build();

You can also disable local caching entirely; bear in mind that, in this case, every flag check will result in a network request:

1 import com.schematic.api.Schematic;
2 import java.util.Collections;
3 
4 Schematic schematic = Schematic.builder()
5     .apiKey("YOUR_API_KEY")
6     .cacheProviders(Collections.emptyList())
7     .build();

You may want to specify default flag values for your application, which will be used if there is a service interruption or if the client is running in offline mode:

1 import com.schematic.api.Schematic;
2 import java.util.HashMap;
3 import java.util.Map;
4 
5 Map<String, Boolean> flagDefaults = new HashMap<>();
6 flagDefaults.put("some-flag-key", true);
7 
8 Schematic schematic = Schematic.builder()
9     .apiKey("YOUR_API_KEY")
10     .flagDefaults(flagDefaults)
11     .build();

Offline Mode

In development or testing environments, you may want to avoid making network requests when checking flags or submitting events. You can run Schematic in offline mode:

1 import com.schematic.api.Schematic;
2 
3 Schematic schematic = Schematic.builder()
4     .apiKey("YOUR_API_KEY")
5     .offline(true)
6     .build();

When in offline mode:

Flag checks will return the default value for the flag being checked (false by default, or as specified in flagDefaults)
Events (identify and track) will be skipped completely
All other API calls will use a no-op HTTP client that doesn’t make actual network requests, returning empty responses

This is especially useful for development, testing, or when running unit tests that shouldn’t depend on the Schematic API.

Offline mode works well with flag defaults:

1 import com.schematic.api.Schematic;
2 import java.util.HashMap;
3 import java.util.Map;
4 
5 Map<String, Boolean> flagDefaults = new HashMap<>();
6 flagDefaults.put("some-flag-key", true);
7 
8 Schematic schematic = Schematic.builder()
9     .apiKey("YOUR_API_KEY")
10     .offline(true)
11     .flagDefaults(flagDefaults)
12     .build();
13 
14 boolean flagValue = schematic.checkFlag("some-flag-key", null, null); // Returns true

Event Buffer

Schematic API uses an Event Buffer to batch Identify and Track requests and avoid multiple API calls. You can set the event buffer flush period:

1 import com.schematic.api.Schematic;
2 import java.time.Duration;
3 
4 Schematic schematic = Schematic.builder()
5     .apiKey("YOUR_API_KEY")
6     .eventBufferInterval(Duration.ofSeconds(5))
7     .build();

Exception Handling

When the API returns a non-success status code (4xx or 5xx response), a subclass of SchematicException will be thrown.

1 import com.schematic.api.core.SchematicException;
2 
3 try {
4     schematic.companies().getCompany(...);
5 } catch (SchematicException e) {
6     System.out.println(e.message());
7 }

The SDK also supports error handling for first class exceptions with strongly typed body fields.

1 import com.schematic.api.errors.InvalidRequestError;
2 
3 try {
4     schematic.companies().getCompany(...);
5 } catch (InvalidRequestError e) {
6     System.out.println(e.message());
7     System.out.println(e.getBody().getMissingField());
8 }

Retries

The SDK is instrumented with automatic retries with exponential backoff. A request will be retried as long as the request is deemed retriable and the number of retry attempts has not grown larger than the configured retry limit (default: 2).

A request is deemed retriable when any of the following HTTP status codes is returned:

408 (Timeout)
429 (Too Many Requests)
5XX (Internal Server Errors)

DataStream

DataStream enables local flag evaluation by maintaining a WebSocket connection to Schematic and caching flag rules, company, and user data locally. This reduces latency and network calls for flag checks.

Key Features

Real-Time Updates: Automatically updates cached data when changes occur on the backend.
Configurable Caching: Supports both in-memory (local) caching and Redis-based caching.
Efficient Flag Checks: Flag evaluation happens locally using a WASM rules engine.

Setup

1 import com.schematic.api.Schematic;
2 import com.schematic.api.datastream.DatastreamOptions;
3 
4 Schematic schematic = Schematic.builder()
5     .apiKey("YOUR_API_KEY")
6     .datastreamOptions(DatastreamOptions.builder()
7         .build())
8     .build();
9 
10 // Flag checks are now evaluated locally
11 boolean flagValue = schematic.checkFlag("some-flag-key", company, user);
12 
13 // When done, close the client to release resources
14 schematic.close();

Configuration Options

Option	Type	Default	Description
`cacheTTL`	`Duration`	24 hours	Cache TTL for flag/company/user data
`redisCache`	`RedisCacheConfig`	—	Redis connection config (uses in-memory cache if not provided)

Configuring Redis Cache

DataStream supports Redis for caching, which is required for Replicator Mode. Pass a RedisCacheConfig and the SDK will create and manage the Redis connection internally:

1 import com.schematic.api.Schematic;
2 import com.schematic.api.cache.RedisCacheConfig;
3 import com.schematic.api.datastream.DatastreamOptions;
4 import java.time.Duration;
5 
6 Schematic schematic = Schematic.builder()
7     .apiKey("YOUR_API_KEY")
8     .datastreamOptions(DatastreamOptions.builder()
9         .redisCache(RedisCacheConfig.builder()
10             .endpoint("localhost:6379")
11             .keyPrefix("schematic:")
12             .build())
13         .cacheTTL(Duration.ofMinutes(5))
14         .build())
15     .build();

Redis Configuration Options

Option	Type	Default	Description
`endpoint`	`String`	`localhost:6379`	Redis server address in `host:port` format
`endpoints`	`List<String>`	`["localhost:6379"]`	Multiple endpoints (for future cluster support)
`username`	`String`	—	Redis 6.0+ ACL username
`password`	`String`	—	Redis password
`database`	`int`	`0`	Redis database index
`ssl`	`boolean`	`false`	Enable SSL/TLS
`keyPrefix`	`String`	`schematic:`	Prefix for all Redis cache keys
`connectTimeout`	`Duration`	5 seconds	Connection timeout
`readTimeout`	`Duration`	3 seconds	Read timeout
`maxPoolSize`	`int`	8	Maximum connection pool size

Replicator Mode

Replicator mode is designed for environments where a separate process (the schematic-datastream-replicator) manages the WebSocket connection and populates a shared Redis cache. The SDK reads from that cache and evaluates flags locally without establishing its own WebSocket connection.

Requirements

Replicator mode requires Redis as a shared cache so the SDK can read data written by the external replicator process. An in-memory cache will not work since the replicator and SDK run in separate processes.

Setup

1 import com.schematic.api.Schematic;
2 import com.schematic.api.cache.RedisCacheConfig;
3 import com.schematic.api.datastream.DatastreamOptions;
4 
5 Schematic schematic = Schematic.builder()
6     .apiKey("YOUR_API_KEY")
7     .datastreamOptions(DatastreamOptions.builder()
8         .redisCache(RedisCacheConfig.builder()
9             .endpoint("localhost:6379")
10             .build())
11         .withReplicatorMode("http://localhost:8090/ready")
12         .build())
13     .build();

Configuration Options

Option	Type	Default	Description
`withReplicatorMode`	`String`	—	Enables replicator mode with the given health check URL
`redisCache`	`RedisCacheConfig`	—	Required. Redis connection config for the shared cache
`replicatorHealthCheckInterval`	`Duration`	30 seconds	Health check polling interval
`cacheTTL`	`Duration`	24 hours	Cache TTL (should match the replicator’s TTL)

Cache TTL Configuration

Important: When using Replicator Mode, you should set the SDK’s cache TTL to match the replicator’s cache TTL. The replicator defaults to an unlimited cache TTL. If the SDK uses a shorter TTL (the default is 24 hours), locally updated cache entries (e.g. after track events) will be written back with the shorter TTL and eventually evicted from the shared Redis cache, even though the replicator originally set them with no expiration.

To match the replicator’s default unlimited TTL:

1 DatastreamOptions.builder()
2     .redisCache(RedisCacheConfig.builder()
3         .endpoint("localhost:6379")
4         .build())
5     .withReplicatorMode("http://localhost:8090/ready")
6     .cacheTTL(Duration.ZERO) // Unlimited, matching the replicator default
7     .build()

When running in Replicator Mode, the client will:

Skip establishing WebSocket connections
Periodically check if the replicator service is ready
Use cached data populated by the external replicator service
Fall back to direct API calls if the replicator is not available

Contributing

While we value open-source contributions to this SDK, this library is generated programmatically. Additions made directly to this library would have to be moved over to our generation code, otherwise they would be overwritten upon the next generated release. Feel free to open a PR as a proof of concept, but know that we will not be able to merge it as-is. We suggest opening an issue first to discuss with us!

On the other hand, contributions to the README are always very welcome!