Build, query, and operate enterprise search from one control plane.
NextSearch brings cluster health, index administration, Query DSL, hybrid retrieval, connected data workspaces, and an AI copilot into one operator experience. Nextbrick consultants use the same search-engineering discipline to assess, modernize, and migrate Elasticsearch, OpenSearch, and Apache Solr workloads.
3,174
Queries per second
39.41 ms
Measured p99 latency
327 MiB
RAM snapshot
1 JAR
Deployable runtime
Benchmark figures are from the existing same-hardware NextSearch comparison published by NextBricks.
Benchmark preview
Two representative pages are available here. The complete benchmark deck, test context, and connected-platform evidence are available through the business download form.
A direct comparison of throughput, p99 latency, requests served, and memory footprint across NextSearch, Elasticsearch, OpenSearch, and Solr.
Operational evidence from the connected Agentic AI workspace, including model selection, prompt history, measured latency, and execution timestamps.
Product and engineering evidence
Current console views show how teams operate search workloads. The contribution summaries document selected upstream work across the search technologies Nextbrick supports.
A full console view of cluster health, nodes, shards, indexes, templates, data streams, ingest pipelines, and the JDPA workspace.
The operator surface brings system status, cores, Query and JSON Request APIs, schema controls, analysis, configuration, and dense-vector workflows together.
A focused production view for cluster metrics, workload management, data sources, collections, security, ingestion, integrations, and operations.
Published contribution evidence across Apache Solr, Apache Lucene, OpenSearch, and Drupal, including reliability, scoring, build, and project-resilience work.
A detailed view of selected pull requests, merge requests, reviewer feedback, approvals, and project outcomes from the NextBricks engineering team.
Technical library
Read engineering analysis behind selected upstream contributions, plus customer demo and implementation guides for NextSearch, NextCMS, and NextLLM workflows.
An 11-page technical review of test-cluster distribution isolation and Gradle immutable transform-cache safety, including implementation rationale and validation evidence.
A 3-page contribution brief covering stable schema snapshots during request processing, the affected call paths, implementation scope, and focused test results.
A 2-page implementation and validation report for five Solr Admin UI defects spanning navigation, Collections, Schema Designer, core health, and reload feedback.
An 8-page contribution brief explaining session-expiration-aware ZooKeeper recovery, component-owned AtomicBoolean state, transition behavior, and test evidence.
A 9-page technical review of the revised recovery ownership model, reviewer request, state transitions, implementation details, and repository validation.
Customer demos and benchmarks
A 4-page public guide to the Wesco catalog and AI assistant, NextSearch 2.3 workspace, NextCMS content operations, and NextLLM workflows. Demo credentials are removed from this public edition.
A 21-page demo and benchmark deck covering the Wesco experience, the connected NextBricks platform, NextSearch, NextCMS, NextLLM, and supporting product evidence.
Consulting and production support
Nextbrick supports search teams before, during, and after deployment. Engagements can cover a focused production issue, a platform assessment, an upgrade or migration, or ongoing engineering and operational support.
OpenSearch consulting, OpenSearch support, migrations, upgrades, security, performance tuning, cost optimization, and production operations for managed and self-hosted clusters.
View serviceElasticsearch support, Elastic Search support, incident response, cluster recovery, upgrades, capacity planning, relevance engineering, and ongoing Elasticsearch support services.
View serviceSolr consulting, Solr consulting services, Solr support, and Solr support services covering SolrCloud, relevance, schema design, upgrades, scaling, and production troubleshooting.
View serviceLucidworks Fusion consulting and Lucidworks Fusion support for application design, connectors, indexing, signals, relevance, upgrades, migration, and operations.
View serviceCoveo consulting for enterprise search, ecommerce discovery, content sources, indexing pipelines, relevance, analytics, integrations, and platform modernization.
View serviceAI agent consulting for retrieval-augmented generation, agent tools, governed knowledge access, evaluation, observability, safety controls, and production deployment.
View serviceNextSearch software
NextSearch combines search-engine administration, migration testing, relevance work, vector retrieval, RAG workflows, and AI-assisted operations in one deployable software platform.
One operating flow
Bring product catalogs, documents, CMS content, application data, and enterprise sources into a governed workspace.
Create and inspect indexes, aliases, shards, templates, data streams, and ingestion pipelines from one console.
Validate compatibility and relevance with Query DSL, lexical retrieval, vector search, and neural-search controls.
Track cluster health, manage environments, open connected dashboards, and use the copilot to accelerate routine work.
Nextbrick search practice
NextSearch is the product layer. Nextbrick is the consulting and delivery team behind architecture assessments, migrations, performance work, relevance engineering, AI retrieval, and production support. Each technology has a dedicated service page so buyers and search engines can find the exact expertise they need.
Architecture, upgrades, performance, relevance, vector search, Elastic Cloud, and production support for Elasticsearch workloads.
Amazon OpenSearch Service and self-managed OpenSearch architecture, migration, security, hybrid search, cost optimization, and operations.
SolrCloud design, schema and analyzer work, performance tuning, relevance engineering, upgrades, migrations, and managed support.
Migration and modernization
Search migration is not a one-click index copy. Query behavior, analyzers, mappings or schemas, plugins, clients, pipelines, dashboards, security, and operating procedures all need explicit compatibility and acceptance criteria.
Decision before migration
We first determine whether to optimize, upgrade, migrate to another engine, or evaluate NextSearch.
Capture versions, plugins, schemas or mappings, clients, pipelines, indexes, query patterns, security, data volume, and service objectives.
Measure representative indexing throughput, p95 and p99 latency, relevance judgments, resource use, failure modes, and operating cost.
Compare APIs, query behavior, analyzers, aggregations, lifecycle controls, dashboards, security, and operational dependencies.
Move production-shaped data, replay traffic, compare results, test recovery, validate observability, and document rollback conditions.
Synchronize changes, route traffic in controlled stages, monitor acceptance criteria, and retain a tested rollback window.
Close migration debt, tune from real workload evidence, document ownership, and establish capacity, patching, and upgrade routines.
Source
Elasticsearch, OpenSearch, Solr, or a legacy search platform
Acceptance
Data fidelity, API behavior, relevance, latency, throughput, security, and recovery
Outcome
A tested target, cutover runbook, rollback plan, and documented ownership
Inside the product
Each screen below comes from the working NextSearch application.
Product view 1
Monitor nodes, shards, index counts, and version footprint while the embedded NextLLM Copilot answers operational questions against the connected search environment.
Product view 2
Inspect index inventory, synchronize the catalog with NextCMS and NextLLM, and carry out common navigation and administration tasks without leaving the console.
Product view 3
Run match-all, count, field-capability, and custom JSON queries in a focused playground designed for migration testing and day-to-day search engineering.
Product view 4
Move between customer or application workspaces, check index health, and open the connected dashboards or content-management surface from the same operator flow.
Core capabilities
Use NextSearch as the retrieval layer for customer-facing search, internal knowledge, or AI applications.
Lexical, vector, and neural-search surfaces support product discovery, enterprise knowledge search, and RAG retrieval.
Manage clusters, nodes, indexes, shards, aliases, templates, data streams, and search pipelines from one interface.
Use an embedded assistant with selectable data sources and task shortcuts for health checks, index discovery, and administration.
Exercise Query DSL and inspect live index behavior while moving workloads from Elasticsearch, OpenSearch, or Solr.
Experience and evidence
Nextbrick has more than 15 years of enterprise search experience across performance, relevance, ecommerce discovery, content integration, multilingual retrieval, and production operations. NextSearch turns that delivery experience into a product teams can inspect and evaluate directly.
A published multilingual search and AI delivery story spanning more than 30,000 pages, Salesforce integration, retrieval, and live analytics.
View evidencePublished customer work across Solr, Lucidworks, Elasticsearch, content discovery, ecommerce search, and enterprise knowledge experiences.
View evidenceA named leadership team and a public company history grounded in enterprise software, search engineering, cloud operations, AI, and delivery.
View evidenceDirect answers
Clear answers for buyers, technical evaluators, search engines, and AI assistants assessing NextSearch and Nextbrick consulting services.
NextSearch is an enterprise search operations and migration platform from NextBricks. It combines index administration, Query DSL testing, cluster health, lexical and vector retrieval, connected data workspaces, and an embedded NextLLM Copilot.
Yes. Nextbrick provides Elasticsearch architecture, implementation, upgrades, performance tuning, search relevance, vector and hybrid search, Elastic Cloud guidance, and production support. NextSearch can be used as an evaluation and migration workspace when a team is considering modernization or replacement.
Yes. Nextbrick supports Amazon OpenSearch Service and self-managed OpenSearch, including cluster design, Elasticsearch migration, security, performance, cost optimization, neural and hybrid search, observability, upgrades, and ongoing operations.
Yes. Nextbrick provides Solr and SolrCloud architecture, schema and analyzer design, relevance tuning, performance optimization, upgrades, migration, custom development, and production support.
Yes. Nextbrick provides OpenSearch support for Amazon OpenSearch Service and self-managed deployments, including production incidents, cluster health, upgrades, security, shard strategy, performance tuning, cost optimization, observability, and ongoing operations.
Nextbrick Elasticsearch support services cover architecture reviews, production troubleshooting, cluster recovery, version upgrades, capacity planning, indexing and query performance, search relevance, Elastic Cloud, vector search, observability, and operational runbooks.
Yes. Solr support and Solr consulting services include SolrCloud architecture, schema and analyzer design, relevance tuning, indexing and query performance, upgrades, migration planning, incident response, capacity planning, and production operations.
Yes. Nextbrick provides Lucidworks Fusion consulting and Lucidworks Fusion support for application architecture, connectors, indexing pipelines, signals, relevance, upgrades, migration, troubleshooting, and ongoing platform operations.
Yes. Nextbrick provides Coveo consulting for enterprise search and ecommerce discovery, plus AI agent consulting for RAG retrieval, governed knowledge access, agent tools, evaluation, observability, and production deployment.
No responsible migration should be treated as one-click. NextSearch helps teams inspect indexes, test Query DSL, compare behavior, and operate the target environment, while Nextbrick consultants assess compatibility, rehearse data and traffic movement, define acceptance criteria, and build a rollback plan.
Useful inputs include the current engine and version, hosting model, data and index volume, query and ingest rates, latency targets, relevance requirements, plugins, integrations, security constraints, availability objectives, budget, and timeline.
Migration recommendations are checked against current vendor and project documentation for the customer's exact source and target versions.
Plan your rollout
Share your current engine, index volume, query traffic, latency target, relevance requirements, security constraints, budget, and timeline. We will turn that into a practical evaluation and migration plan.
