Databases · head to head
QuestDB vs Teradata
QuestDB
Databases
Fast open source time-series database for high throughput ingestion
- From
- Free
- Rated
- -
Teradata
Databases
Long-established enterprise MPP data warehouse, rebranded in 2026 as the Autonomous Knowledge Platform, sold for cloud, on-premises and hybrid.
- From
- On request
- Rated
- -
The short version
- Only QuestDB has a free tier, so it costs nothing to try first.
- Each has a real cost: QuestDB open-source edition lacks high-availability, distributed architecture, and enterprise security features; Teradata licensing is negotiated rather than published, so there is no way to compare total cost against a consumption-priced warehouse without entering a sales cycle, and the comparison is only ever as good as the workload profile you gave them.
- They diverge on capability: QuestDB covers High Throughput Ingestion, Teradata covers Massively parallel architecture.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which QuestDB and Teradata actually diverge.
Identical on both: user rating (Not yet rated), category (Databases).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in QuestDB
- High Throughput Ingestion
- SQL Support
- Time-series Optimization
- SIMD Vectorization
- Column-oriented Storage
- Built-in Web Console
- InfluxDB Line Protocol
- PostgreSQL
Only in Teradata
- Massively parallel architecture
- Workload management
- Mature cost-based optimiser
- Cloud, on-premises and hybrid
- Bulk load utilities
- BTEQ scripting
- In-database analytics
- Enterprise Vector Store
What people use each for
The jobs each tool is most often brought in to do.
QuestDB
- Time-series analytics ingesting up to 20M rows/second from IoT sensors or financial data feedsnot Teradata
- Real-time dashboarding with 32ms time-to-first-row latency for minute-level analyticsnot Teradata
- Applications requiring multi-tier storage (hot ingest, real-time SQL, cold Parquet archive)not Teradata
Teradata
- A large existing Teradata estate where the practical question is which workloads to migrate first rather than whether to adoptnot QuestDB
- High-concurrency mixed workloads where hundreds of analysts and scheduled jobs contend and predictable prioritisation matters more than peak single-query speednot QuestDB
- Regulated reporting where the same query must produce the same answer for years and the audit trail of the existing implementation has valuenot QuestDB
- Hybrid deployments where regulatory or data-residency rules keep a portion of the warehouse on-premises while the rest moves to cloudnot QuestDB
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
QuestDB
- Open-source edition lacks high-availability, distributed architecture, and enterprise security features
- Enterprise edition pricing not published; requires contacting sales for custom quote
- Ingestion limit of 20M rows/sec platform-dependent; may not scale to extreme throughput requirements
Teradata
- Licensing is negotiated rather than published, so there is no way to compare total cost against a consumption-priced warehouse without entering a sales cycle, and the comparison is only ever as good as the workload profile you gave them.
- The SQL dialect and the loading utilities are Teradata-specific, so every stored procedure, macro and BTEQ script written against the platform is migration debt that grows with each release you ship.
- Primary index choice determines data distribution, and a poorly chosen index concentrates rows on a few processing units, which surfaces as one slow query rather than an error and needs a specialist to diagnose.
- The skills market is contracting, so DBA and workload-management expertise is expensive to hire, hard to replace when someone retires, and increasingly hard to buy from consultancies whose own bench has moved to cloud warehouses.
- The 2026 renaming of Vantage, VantageCloud, ClearScape and QueryGrid split documentation, runbooks and vendor material across two naming systems, so searching for an error or a configuration now returns results for a product that is described under a different name.
Pricing, plan by plan
QuestDB
FreeNo published plan breakdown. See the QuestDB review.
Teradata
On requestNo published plan breakdown. See the Teradata review.
Which should you pick?
Choose QuestDB if
- You need high throughput ingestion.
- You want to start without paying.
- You work on Docker, Kubernetes, Cloud (AWS, Azure, GCP).
- You also want sql support.
Choose Teradata if
- You need massively parallel architecture.
- You also want workload management.
Questions people ask
- Is QuestDB or Teradata better?
- Neither clearly leads. QuestDB starts at Free and Teradata at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, QuestDB or Teradata?
- QuestDB has a free tier; the other does not. Paid plans start at Free for QuestDB and On request for Teradata.
- Does QuestDB or Teradata run on more platforms?
- QuestDB runs on Docker, Kubernetes, Cloud (AWS, Azure, GCP). Teradata runs on Web.
- Can I use QuestDB for free?
- Yes. QuestDB has a free tier, so you can try it without paying. Teradata starts at On request.
- What is QuestDB best used for?
- QuestDB is most often used for time-series analytics ingesting up to 20m rows/second from iot sensors or financial data feeds, real-time dashboarding with 32ms time-to-first-row latency for minute-level analytics, applications requiring multi-tier storage (hot ingest, real-time sql, cold parquet archive). Of those, time-series analytics ingesting up to 20m rows/second from iot sensors or financial data feeds and real-time dashboarding with 32ms time-to-first-row latency for minute-level analytics are not what Teradata is typically brought in for.
- What can QuestDB do that Teradata cannot?
- QuestDB covers High Throughput Ingestion, SQL Support, Time-series Optimization, SIMD Vectorization. Teradata covers Massively parallel architecture, Workload management, Mature cost-based optimiser, Cloud, on-premises and hybrid.
Answered from the vendors’ own pages
QuestDB: How much does QuestDB Enterprise cost?
QuestDB does not publish specific pricing for the Enterprise tier. Customers must contact QuestDB via their enterprise contact form to receive a custom quote.
SourceTeradata: Is Teradata only on-premises?
No. It is sold for cloud, on-premises and hybrid deployment, and the cloud offering is now branded Teradata Cloud. A large part of the installed base is still on-premises or hybrid.
QuestDB: Does QuestDB offer a free version?
Yes, QuestDB Open Source is completely free and recommended for evaluation, prototyping, and pilot projects. Enterprise features, high availability, security, and dedicated support require the paid Enterprise tier.
SourceTeradata: How does it compare to Snowflake or BigQuery?
On raw elasticity and cost transparency the cloud warehouses win. On mixed-workload concurrency management against a large existing query estate Teradata is still hard to replace, which is why migrations off it take years rather than quarters.
QuestDB: What deployment options does QuestDB offer?
QuestDB offers open source deployment, Enterprise deployment, and Bring Your Own Cloud (BYOC) deployment. Pricing details for BYOC and Enterprise tiers are not published and require direct contact with sales.
SourceTeradata: Why do organisations stay on it?
Because the cost of leaving is the estate, not the data. Thousands of procedures, scripts and extracts written in a proprietary dialect have to be rewritten and revalidated, and in regulated reporting that revalidation is the expensive part.
Teradata: What changed in the 2026 rebrand?
Vantage became the Autonomous Knowledge Platform, VantageCloud became Teradata Cloud, ClearScape Analytics became AI Studio and QueryGrid became Fabric. The underlying products are continuous with what came before.
Teradata: Can it handle AI and vector workloads?
It has added an Enterprise Vector Store and in-database analytics branded AI Studio. Whether that is preferable to moving the data into a purpose-built vector store depends on how much of your data already lives in the warehouse.
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