timescale · billy-the-fish · Jan 14, 2026 · Jan 9, 2026 · Jan 14, 2026 · Jan 14, 2026
diff --git a/api-reference/pgai/model-calling/openai/openai_chat_complete.mdx b/api-reference/pgai/model-calling/openai/openai_chat_complete.mdx
@@ -7,7 +7,7 @@ license: community
 type: function
 ---
 
-import OpenAPIChatComplete from '/snippets/api-reference/pgai/_openai_chat_complete_arguments.mdx';
+import OpenAPIChatComplete from '/snippets/reference/pgai/_openai_chat_complete_arguments.mdx';
 
 Generate text completions using OpenAI's chat models like GPT-4 and GPT-3.5. This function enables you to have
 multi-turn conversations, generate text from prompts, and leverage advanced language model capabilities directly from

diff --git a/api-reference/pgai/model-calling/openai/openai_chat_complete_with_raw_response.mdx b/api-reference/pgai/model-calling/openai/openai_chat_complete_with_raw_response.mdx
@@ -7,7 +7,7 @@ license: community
 type: function
 ---
 
-import OpenAPIChatComplete from '/snippets/api-reference/pgai/_openai_chat_complete_arguments.mdx';
+import OpenAPIChatComplete from '/snippets/reference/pgai/_openai_chat_complete_arguments.mdx';
 
 Generate chat completions and receive the raw HTTP response. Use this when you need access to HTTP headers,
 status codes, or other low-level response details.

diff --git a/api-reference/pgai/model-calling/openai/openai_embed.mdx b/api-reference/pgai/model-calling/openai/openai_embed.mdx
@@ -7,7 +7,7 @@ license: community
 type: function
 ---
 
-import OpenAPIEmbedArguments from '/snippets/api-reference/pgai/_openai_embed_arguments.mdx';
+import OpenAPIEmbedArguments from '/snippets/reference/pgai/_openai_embed_arguments.mdx';
 
 Generate vector embeddings from text, text arrays, or tokens using OpenAI's embedding models. Embeddings are numerical
 representations of text that capture semantic meaning, making them ideal for semantic search, recommendations, and

diff --git a/api-reference/pgai/model-calling/openai/openai_embed_with_raw_response.mdx b/api-reference/pgai/model-calling/openai/openai_embed_with_raw_response.mdx
@@ -7,7 +7,7 @@ license: community
 type: function
 ---
 
-import OpenAPIEmbedArguments from '/snippets/api-reference/pgai/_openai_embed_arguments.mdx';
+import OpenAPIEmbedArguments from '/snippets/reference/pgai/_openai_embed_arguments.mdx';
 
 Generate embeddings and receive the complete raw API response including all metadata. Use this when you need access to
 token usage, model information, or other response details not included in the standard `openai_embed()` function.

diff --git a/api-reference/pgai/model-calling/openai/openai_list_models.mdx b/api-reference/pgai/model-calling/openai/openai_list_models.mdx
@@ -7,7 +7,7 @@ license: community
 type: function
 ---
 
-import OpenAPIListModels from '/snippets/api-reference/pgai/_openai_list_models_arguments.mdx';
+import OpenAPIListModels from '/snippets/reference/pgai/_openai_list_models_arguments.mdx';
 
 Retrieve a list of all models available from OpenAI, including their creation dates and ownership information. This is
 useful for discovering available models and verifying access to specific models.

diff --git a/api-reference/pgai/model-calling/openai/openai_list_models_with_raw_response.mdx b/api-reference/pgai/model-calling/openai/openai_list_models_with_raw_response.mdx
@@ -7,7 +7,7 @@ license: community
 type: function
 ---
 
-import OpenAPIListModels from '/snippets/api-reference/pgai/_openai_list_models_arguments.mdx';
+import OpenAPIListModels from '/snippets/reference/pgai/_openai_list_models_arguments.mdx';
 
 List available models and receive the raw HTTP response. Use this when you need access to HTTP headers, status codes,
 or other low-level response details.

diff --git a/api-reference/pgai/model-calling/openai/openai_moderate.mdx b/api-reference/pgai/model-calling/openai/openai_moderate.mdx
@@ -7,7 +7,7 @@ license: community
 type: function
 ---
 
-import OpenAPIModerate from '/snippets/api-reference/pgai/_openai_moderate_arguments.mdx';
+import OpenAPIModerate from '/snippets/reference/pgai/_openai_moderate_arguments.mdx';
 
 Analyze text content to detect potential policy violations including hate speech, violence, sexual content, self-harm,
 and harassment. This uses OpenAI's moderation API to help ensure your application complies with usage policies.

diff --git a/api-reference/pgai/model-calling/openai/openai_moderate_with_raw_response.mdx b/api-reference/pgai/model-calling/openai/openai_moderate_with_raw_response.mdx
@@ -7,7 +7,7 @@ license: community
 type: function
 ---
 
-import OpenAPIModerate from '/snippets/api-reference/pgai/_openai_moderate_arguments.mdx';
+import OpenAPIModerate from '/snippets/reference/pgai/_openai_moderate_arguments.mdx';
 
 Moderate content and receive the raw HTTP response. Use this when you need access to HTTP headers, status codes, or
 other low-level response details.

diff --git a/api-reference/timescaledb-toolkit/candlestick_agg/index.mdx b/api-reference/timescaledb-toolkit/candlestick_agg/index.mdx
@@ -4,7 +4,7 @@ description: Perform analysis of financial asset data
 sidebarTitle: Overview
 ---
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 Perform analysis of financial asset data. These specialized hyperfunctions make
 it easier to write financial analysis queries that involve candlestick data.

diff --git a/api-reference/timescaledb-toolkit/counters-and-gauges/counter_agg/index.mdx b/api-reference/timescaledb-toolkit/counters-and-gauges/counter_agg/index.mdx
@@ -14,7 +14,7 @@ Analyze data whose values are designed to monotonically increase, and where any
 
 If it's possible for your readings to decrease as well as increase, use [`gauge_agg`][gauge_agg] instead.
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb-toolkit/counters-and-gauges/gauge_agg/index.mdx b/api-reference/timescaledb-toolkit/counters-and-gauges/gauge_agg/index.mdx
@@ -13,7 +13,7 @@ Analyze data coming from gauges. Unlike counters, gauges can decrease as well as
 
 If your value can only increase, use [`counter_agg`][counter_agg] instead to appropriately account for resets.
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb-toolkit/counters-and-gauges/index.mdx b/api-reference/timescaledb-toolkit/counters-and-gauges/index.mdx
@@ -16,7 +16,7 @@ calculate rates, deltas, and trends from time-series measurements.
   (for example, request counts, bytes sent)
 - **Gauges**: Analyze data that can both increase and decrease (for example, temperature, memory usage, queue depth)
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb-toolkit/frequency-analysis/count_min_sketch/index.mdx b/api-reference/timescaledb-toolkit/frequency-analysis/count_min_sketch/index.mdx
@@ -16,7 +16,7 @@ CPU time and memory, especially for large datasets.
 The count-min sketch produces a biased estimator of frequency. It might overestimate the item count, but it can't
 underestimate. You can control the relative error and the probability that the estimate falls outside the error bounds.
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb-toolkit/frequency-analysis/freq_agg/index.mdx b/api-reference/timescaledb-toolkit/frequency-analysis/freq_agg/index.mdx
@@ -15,7 +15,7 @@ This group of functions contains two aggregate functions, which let you set the
 
 To estimate the absolute number of times a value appears, use [`count_min_sketch`][count_min_sketch].
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb-toolkit/frequency-analysis/index.mdx b/api-reference/timescaledb-toolkit/frequency-analysis/index.mdx
@@ -18,7 +18,7 @@ TimescaleDB Toolkit provides two approaches to frequency analysis:
 -  **count_min_sketch**: Estimate the absolute number of times a specific value appears using the count-min sketch data
   structure
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb-toolkit/hyperloglog/index.mdx b/api-reference/timescaledb-toolkit/hyperloglog/index.mdx
@@ -4,7 +4,7 @@ description: Estimate the number of distinct values in a dataset, also known as
 sidebarTitle: Overview
 ---
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 For large datasets and datasets with high cardinality (many distinct values), this can be much more efficient in
 both CPU and memory than an exact count using `count(DISTINCT)`.

diff --git a/api-reference/timescaledb-toolkit/minimum-and-maximum/index.mdx b/api-reference/timescaledb-toolkit/minimum-and-maximum/index.mdx
@@ -4,7 +4,7 @@ description: Find the smallest and largest values in a dataset
 sidebarTitle: Overview
 ---
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 Find the smallest and largest values in a dataset. These specialized hyperfunctions make
 it easier to write queries that identify extreme values in your data.

diff --git a/api-reference/timescaledb-toolkit/minimum-and-maximum/max_n/index.mdx b/api-reference/timescaledb-toolkit/minimum-and-maximum/max_n/index.mdx
@@ -4,7 +4,7 @@ description: Get the N largest values from a column
 sidebarTitle: Overview
 ---
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 Get the N largest values from a column.
 

diff --git a/api-reference/timescaledb-toolkit/minimum-and-maximum/max_n_by/index.mdx b/api-reference/timescaledb-toolkit/minimum-and-maximum/max_n_by/index.mdx
@@ -4,7 +4,7 @@ description: Get the N largest values with accompanying data
 sidebarTitle: Overview
 ---
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 Get the N largest values from a column, with an associated piece of data per
 value. For example, you can return an accompanying column, or the full row.

diff --git a/api-reference/timescaledb-toolkit/minimum-and-maximum/min_n/index.mdx b/api-reference/timescaledb-toolkit/minimum-and-maximum/min_n/index.mdx
@@ -4,7 +4,7 @@ description: Get the N smallest values from a column
 sidebarTitle: Overview
 ---
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 Get the N smallest values from a column.
 

diff --git a/api-reference/timescaledb-toolkit/minimum-and-maximum/min_n_by/index.mdx b/api-reference/timescaledb-toolkit/minimum-and-maximum/min_n_by/index.mdx
@@ -4,7 +4,7 @@ description: Get the N smallest values with accompanying data
 sidebarTitle: Overview
 ---
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 Get the N smallest values from a column, with an associated piece of data per
 value. For example, you can return an accompanying column, or the full row.

diff --git a/api-reference/timescaledb-toolkit/percentile-approximation/index.mdx b/api-reference/timescaledb-toolkit/percentile-approximation/index.mdx
@@ -16,7 +16,7 @@ TimescaleDB Toolkit provides two advanced percentile approximation algorithms:
 - **UddSketch**: Produces stable estimates within a guaranteed relative error
 - **t-digest**: More accurate at extreme quantiles, though somewhat dependent on input order
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb-toolkit/percentile-approximation/tdigest/index.mdx b/api-reference/timescaledb-toolkit/percentile-approximation/tdigest/index.mdx
@@ -23,7 +23,7 @@ The other advanced percentile approximation aggregate is [`uddsketch`][uddsketch
 within a guaranteed relative error. If you aren't sure which to use, try the default percentile estimation method,
 [`percentile_agg`][percentile_agg]. It uses the `uddsketch` algorithm with some sensible defaults.
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb-toolkit/percentile-approximation/uddsketch/index.mdx b/api-reference/timescaledb-toolkit/percentile-approximation/uddsketch/index.mdx
@@ -22,7 +22,7 @@ quantiles, but is somewhat dependent on input order.
 If you aren't sure which aggregate to use, try the default percentile estimation method,
 [`percentile_agg`][percentile_agg]. It uses the `uddsketch` algorithm with some sensible defaults.
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb-toolkit/state-tracking/index.mdx b/api-reference/timescaledb-toolkit/state-tracking/index.mdx
@@ -17,7 +17,7 @@ TimescaleDB Toolkit provides three approaches to state tracking:
 - **state_agg**: Track state transitions with full timestamp information
 - **heartbeat_agg**: Monitor system liveness based on heartbeat signals
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb-toolkit/statistical-and-regression-analysis/index.mdx b/api-reference/timescaledb-toolkit/statistical-and-regression-analysis/index.mdx
@@ -13,7 +13,7 @@ Perform statistical analysis and linear regression on time-series data. These fu
 statistical aggregates, but they include more features and are easier to use in continuous aggregates and window
 functions.
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/...db-toolkit/statistical-and-regression-analysis/stats_agg-one-variable/index.mdx b/...db-toolkit/statistical-and-regression-analysis/stats_agg-one-variable/index.mdx
@@ -16,7 +16,7 @@ easier to use in continuous aggregates and window functions.
 These functions work on one-dimensional data. To work with two-dimensional data, for example to perform linear
 regression, see [the two-dimensional `stats_agg` functions][stats_agg-2d].
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/...b-toolkit/statistical-and-regression-analysis/stats_agg-two-variables/index.mdx b/...b-toolkit/statistical-and-regression-analysis/stats_agg-two-variables/index.mdx
@@ -18,7 +18,7 @@ fitting method.
 These functions work on two-dimensional data. To work with one-dimensional data, for example to calculate the average
 and standard deviation of a single variable, see [the one-dimensional `stats_agg` functions][stats_agg-1d].
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb-toolkit/time_weight/index.mdx b/api-reference/timescaledb-toolkit/time_weight/index.mdx
@@ -18,7 +18,7 @@ change occurs. The regular mean counts the steady-state reading as only a single
 accounts for the long period of time spent in the steady state. In essence, the time-weighted mean takes an integral
 over time, then divides by the elapsed time.
 
-import TwoStepAggregation from '/snippets/api-reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
+import TwoStepAggregation from '/snippets/reference/timescaledb/hyperfunctions/_two-step-aggregation.mdx';
 
 ## Two-step aggregation
 

diff --git a/api-reference/timescaledb/configuration/gucs.mdx b/api-reference/timescaledb/configuration/gucs.mdx
@@ -4,7 +4,7 @@ description: Optimize the behavior of TimescaleDB using Grand Unified Configurat
 keywords: [GUC, Configuration]
 ---
 
-import TsdbGucsList from '/snippets/api-reference/timescaledb/configuration/_timescaledb-gucs.mdx';
+import TsdbGucsList from '/snippets/reference/timescaledb/configuration/_timescaledb-gucs.mdx';
 import { SERVICE_LONG } from '/snippets/vars.mdx';
 
 You use the following Grand Unified Configuration (GUC) parameters to optimize the behavior of your {SERVICE_LONG}.

diff --git a/api-reference/timescaledb/configuration/tiger-postgres.mdx b/api-reference/timescaledb/configuration/tiger-postgres.mdx
@@ -1,12 +1,11 @@
 ---
-title: TimescaleDB configuration and tuning
-description: Configure the TimescaleDB settings related to policies, query planning and execution, distributed hypertables, and administration
+title: Configuration parameters
+description: Configure your TimescaleDB instance including settings related to memory, workers, disk writes, and transactional locks
 products: [cloud]
-keywords: [configuration, settings]
+keywords: [configuration, settings, memory, workers, parameters]
 tags: [tune]
 ---
 
-import TimescaleDBConfig from '/snippets/api-reference/timescaledb/configuration/_timescaledb-config.mdx';
-import { TIMESCALE_DB } from '/snippets/vars.mdx';
+import ConfigurationParameters from '/snippets/reference/timescaledb/_configuration-parameters.mdx';
 
-<TimescaleDBConfig />
+<ConfigurationParameters />
diff --git a/api-reference/timescaledb/continuous-aggregates/cagg_migrate.mdx b/api-reference/timescaledb/continuous-aggregates/cagg_migrate.mdx
@@ -9,7 +9,7 @@ type: procedure
 products: [cloud, self_hosted, mst]
 ---
 
-import ReturnsVoid from '/snippets/api-reference/timescaledb/_returns-void.mdx';
+import ReturnsVoid from '/snippets/reference/timescaledb/_returns-void.mdx';
 import { CAGG, TIMESCALE_DB } from '/snippets/vars.mdx';
 
 <Icon icon="tag" iconType="duotone" /> Since [2.7.0][tsdb-2.7.0]

diff --git a/api-reference/timescaledb/continuous-aggregates/index.mdx b/api-reference/timescaledb/continuous-aggregates/index.mdx
@@ -6,7 +6,7 @@ keywords: [hypertables, chunks]
 products: [cloud, self_hosted, mst]
 ---
 
-import CaggsIntro from '/snippets/api-reference/timescaledb/continuous-aggregates/_caggs-intro.mdx';
+import CaggsIntro from '/snippets/reference/timescaledb/continuous-aggregates/_caggs-intro.mdx';
 import { CAGG, CAGG_CAP, TIMESCALE_DB, PG, HYPERTABLE } from '/snippets/vars.mdx';
 
 <CaggsIntro />

diff --git a/api-reference/timescaledb/continuous-aggregates/refresh_continuous_aggregate.mdx b/api-reference/timescaledb/continuous-aggregates/refresh_continuous_aggregate.mdx
@@ -8,7 +8,7 @@ type: function
 products: [cloud, self_hosted, mst]
 ---
 
-import ReturnsVoid from '/snippets/api-reference/timescaledb/_returns-void.mdx';
+import ReturnsVoid from '/snippets/reference/timescaledb/_returns-void.mdx';
 import { CAGG, HYPERTABLE } from '/snippets/vars.mdx';
 
 <Icon icon="tag" iconType="duotone" /> Since [1.3.0][tsdb-1.3.0]

diff --git a/...erence/timescaledb/continuous-aggregates/remove_continuous_aggregate_policy.mdx b/...erence/timescaledb/continuous-aggregates/remove_continuous_aggregate_policy.mdx
@@ -9,7 +9,7 @@ type: function
 products: [cloud, self_hosted, mst]
 ---
 
-import ReturnsVoid from '/snippets/api-reference/timescaledb/_returns-void.mdx';
+import ReturnsVoid from '/snippets/reference/timescaledb/_returns-void.mdx';
 import { CAGG, TIMESCALE_DB } from '/snippets/vars.mdx';
 
 <Icon icon="tag" iconType="duotone" /> Since [1.7.0][tsdb-1.7.0]

diff --git a/api-reference/timescaledb/data-retention/remove_retention_policy.mdx b/api-reference/timescaledb/data-retention/remove_retention_policy.mdx
@@ -9,7 +9,7 @@ type: function
 products: [cloud, self_hosted, mst]
 ---
 
-import ReturnsVoid from '/snippets/api-reference/timescaledb/_returns-void.mdx';
+import ReturnsVoid from '/snippets/reference/timescaledb/_returns-void.mdx';
 import {CHUNK, HYPERTABLE} from '/snippets/vars.mdx';
 
 <Icon icon="circle-play" iconType="duotone" /> Community <Icon icon="tag" iconType="duotone" /> Since [1.2.0][tsdb-1.2.0]

diff --git a/api-reference/timescaledb/hypercore/add_columnstore_policy.mdx b/api-reference/timescaledb/hypercore/add_columnstore_policy.mdx
@@ -9,10 +9,10 @@ tags: [scheduled jobs, background jobs, automation framework]
 products: [cloud, mst, self_hosted]
 ---
 
-import OldCreateHypertable from '/snippets/api-reference/timescaledb/hypercore/_old-api-create-hypertable.mdx';
+import OldCreateHypertable from '/snippets/reference/timescaledb/hypercore/_old-api-create-hypertable.mdx';
 import CreateHypertablePolicyNote from
-'/snippets/api-reference/timescaledb/hypercore/_create-hypertable-columnstore-policy-note.mdx';
-import ReturnsVoid from '/snippets/api-reference/timescaledb/_returns-void.mdx';
+'/snippets/reference/timescaledb/hypercore/_create-hypertable-columnstore-policy-note.mdx';
+import ReturnsVoid from '/snippets/reference/timescaledb/_returns-void.mdx';
 import { COLUMNSTORE, ROWSTORE, TIMESCALE_DB, CHUNK, HYPERTABLE, CAGG } from '/snippets/vars.mdx';
 
 <Icon icon="tag" iconType="duotone" /> Since [2.18.0][tsdb-2.18.0]

diff --git a/api-reference/timescaledb/hypercore/convert_to_rowstore.mdx b/api-reference/timescaledb/hypercore/convert_to_rowstore.mdx
@@ -8,8 +8,8 @@ keywords: [columnstore, hypercore, rowstore, chunks, backfilling]
 products: [cloud, mst, self_hosted]
 ---
 
-import HypercoreManualWorkflow from '/snippets/api-reference/timescaledb/hypercore/_hypercore-manual-workflow.mdx';
-import ReturnsVoid from '/snippets/api-reference/timescaledb/_returns-void.mdx';
+import HypercoreManualWorkflow from '/snippets/reference/timescaledb/hypercore/_hypercore-manual-workflow.mdx';
+import ReturnsVoid from '/snippets/reference/timescaledb/_returns-void.mdx';
 import { COLUMNSTORE, ROWSTORE, TIMESCALE_DB, CHUNK, HYPERTABLE } from '/snippets/vars.mdx';
 
 <Icon icon="tag" iconType="duotone" /> Since [2.18.0][tsdb-2.18.0]

diff --git a/api-reference/timescaledb/hypercore/index.mdx b/api-reference/timescaledb/hypercore/index.mdx
@@ -8,8 +8,8 @@ products: [cloud, mst, self_hosted]
 license: community
 ---
 
-import HypercoreIntro from '/snippets/api-reference/timescaledb/hypercore/_hypercore-intro.mdx';
-import OldCreateHypertable from '/snippets/api-reference/timescaledb/hypercore/_old-api-create-hypertable.mdx';
+import HypercoreIntro from '/snippets/reference/timescaledb/hypercore/_hypercore-intro.mdx';
+import OldCreateHypertable from '/snippets/reference/timescaledb/hypercore/_old-api-create-hypertable.mdx';
 import { COLUMNSTORE, HYPERCORE, TIMESCALE_DB, CAGG, CAGG_CAP, HYPERTABLE_CAP } from '/snippets/vars.mdx';
 
 

diff --git a/api-reference/timescaledb/hypercore/remove_columnstore_policy.mdx b/api-reference/timescaledb/hypercore/remove_columnstore_policy.mdx
@@ -9,7 +9,7 @@ tags: [delete, drop]
 products: [cloud, mst, self_hosted]
 ---
 
-import ReturnsVoid from '/snippets/api-reference/timescaledb/_returns-void.mdx';
+import ReturnsVoid from '/snippets/reference/timescaledb/_returns-void.mdx';
 import { COLUMNSTORE, HYPERTABLE, CAGG } from '/snippets/vars.mdx';
 
 <Icon icon="tag" iconType="duotone" /> Since [2.18.0][tsdb-2.18.0]

diff --git a/api-reference/timescaledb/hypertables/add_dimension.mdx b/api-reference/timescaledb/hypertables/add_dimension.mdx
@@ -9,8 +9,8 @@ type: function
 products: [cloud, mst, self_hosted]
 ---
 
-import DimensionInfo from '/snippets/api-reference/timescaledb/hypertables/_dimensions-info.mdx';
-import AddDimensionErrors from '/snippets/api-reference/timescaledb/_add-dimension-errors.mdx';
+import DimensionInfo from '/snippets/reference/timescaledb/hypertables/_dimensions-info.mdx';
+import AddDimensionErrors from '/snippets/reference/timescaledb/_add-dimension-errors.mdx';
 
 import { TIMESCALE_DB, CLOUD_LONG, HYPERTABLE, HYPERTABLE_CAP, CHUNK, PG } from '/snippets/vars.mdx';