Two-way sync
Changes in Apache Hive or Google Cloud Spanner instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Hive and Google Cloud Spanner in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Google Cloud Spanner's rows in Apache Hive, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Google Cloud Spanner where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Google Cloud Spanner sync into Apache Hive in real time, and result tables in Apache Hive sync back into Google Cloud Spanner, with schema and type mapping between the two systems handled for you.
Point analytical queries at the synced copy in Apache Hive and keep Google Cloud Spanner focused on its operational workload.
Rows from Google Cloud Spanner land in Apache Hive as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Apache Hive sync into Google Cloud Spanner, where whatever reads from that database gets them without querying the warehouse.
Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.
| Apache Hive objects | Google Cloud Spanner objects | |
|---|---|---|
| Metastore Catalog The schema registry other engines (Spark, Presto, Impala) also read. | Rows The unit of read and write in each sync cycle, keyed by primary key. | |
| Databases Metastore namespaces that scope tables and grants. | Interleaved tables Child rows physically co-located with parents; synced as related records. | |
| Managed Tables Tables whose data lifecycle Hive controls, used as warehouse destinations. | Secondary indexes Used to make incremental read queries efficient on non-key columns. | |
| External Tables Tables over existing files in HDFS or object storage, read without moving data. | Change streams Capture inserts, updates, and deletes for log-style change data capture. | |
| Partitions Directory-mapped subsets (often by date) that bound incremental sync reads. | Views Read-only projections useful for shaping data before it leaves Spanner. | |
| Views Logical views readable as modeled sources. | Databases Top-level containers that scope schema and sync configuration. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Hive–Google Cloud Spanner connection.
Changes in Apache Hive or Google Cloud Spanner instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Hive or Google Cloud Spanner data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Hive or Google Cloud Spanner record.
Track your Apache Hive ⇄ Google Cloud Spanner sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Hive and Google Cloud Spanner.
Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.
Authenticate Apache Hive and Google Cloud Spanner with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Apache Hive and Google Cloud Spanner objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Apache Hive and Google Cloud Spanner: authenticate both systems, choose the objects to sync (such as Apache Hive's Metastore Catalog and Databases), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Apache Hive: Polling on partition values or timestamp columns; no general-purpose change log for external consumers. On Google Cloud Spanner: Change streams (log-style CDC), or timestamp-based polling queries. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Apache Hive side: External Tables, Partitions, Views, Materialized Views, plus custom fields where Apache Hive exposes them. On the Google Cloud Spanner side: Tables, Rows, Interleaved tables, Secondary indexes. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for Apache Hive and Google Cloud Spanner: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Apache Hive and keep Google Cloud Spanner focused on its operational workload.
Apache Hive: SQL (HiveQL) over JDBC/ODBC via HiveServer2 (Thrift). Authentication: Deployment-dependent: Kerberos, LDAP, or username/password. Google Cloud Spanner: GRPC/REST client API with SQL query surface (GoogleSQL and PostgreSQL-interface dialects). Authentication: Google Cloud IAM (service accounts). Stacksync manages authentication, retries, and rate limits on both sides.
As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Apache Hive and Google Cloud Spanner.