Opensearch for confluence

Offer powerful features for search and analytics. Manticore Search excels in SQL support, real-time indexing, and columnar storage, which can be advantageous for certain use cases. OpenSearch, on the other hand, offers a community-driven ecosystem, anomaly detection, and a fully open-source stack with compatibility for Elasticsearch plugins and APIs up to version 7.10. The best choice depends on your specific project requirements, existing technology stack, and scalability needs.API Client Libraries (SDKs)When it comes to integration with your programming language, both Manticore Search and OpenSearch offer a range of SDKs and tools to help you build powerful search applications. Let’s compare the official SDKs available for both engines.Programming languageManticore SearchOpensearch PHP✓✓ JavaScript✓✓ TypeScript✓✓ Python✓✓ Ruby✗✓ Go✓✓ Rust✗✓ Java✓✓ Elixir✓✗ C++✗✓ C#✓✓Both Manticore Search and Elasticsearch offer a wide range of language support. Elasticsearch has a slight edge in terms of official client libraries, but Manticore Search provides strong integration options as well. Choose the language that best suits your project’s requirements and integrate your preferred search engine seamlessly into your application.External IntegrationsExplore the external integrations and ecosystem compatibility of Manticore Search and OpenSearch, two versatile full-text search engines. This comparison highlights how these solutions interface with various databases, programming languages, and third-party tools, enabling seamless integration into diverse technology stacks and enhancing your search implementation capabilities.Integration nameManticore SearchOpensearchMySQL client support✓✗MySQLdump support✓✗Elasticsearch dump support✓✓Apache Superset integration✓✓Grafana integration✓✓Fluentbit integration✓✓Logstash integration✓✓Filebeat integration✓✓Vector.dev integration✓✓Kibana integration✓✓Kafka integration✓✗Both Manticore Search and OpenSearch offer extensive integration options, allowing them to work harmoniously with a wide range of external services and technologies. OpenSearch has a particularly strong community-driven ecosystem, with tools like OpenSearch Dashboards for data visualization and OpenSearch Ingestion for log and metric collection. Manticore Search offers strong SQL support and compatibility with MySQL-based systems, making it an efficient solution for projects that rely on traditional relational databases.Use CasesManticore Search and OpenSearch are powerful search engines with distinct strengths and capabilities. Understanding their features helps in choosing the right engine for specific use cases. Both engines offer robust full-text search capabilities, but they excel in different areas.E-commerce Search: Both Manticore Search and OpenSearch are strong contenders for e-commerce applications, offering features like faceted search and efficient real-time indexing. Manticore Search stands out with its SQL support, allowing for seamless integration with existing relational databases and enabling developers to use familiar SQL queries. This can significantly reduce development time and complexity. While OpenSearch provides relevance tuning and personalization features, Manticore’s performance optimizations often result in faster search responses, enhancing the user experience in high-traffic online stores.Log Management: OpenSearch is widely recognized for log analysis and monitoring, especially when used within the OpenSearch observability stack (Dashboards, Ingestion). However, Manticore Search offers efficient log searching capabilities, particularly with its columnar storage

Platform notice: Server and Data Center only. This article only applies to Atlassian products on the Server and Data Center platforms.Support for Server* products ended on February 15th 2024. If you are running a Server product, you can visit the Atlassian Server end of support announcement to review your migration options.*Except Fisheye and Crucible SummaryThe OpenSearch instance, which is configured remotely, is experiencing issues with creating indexes for the Bitbucket Data Center. Although the remote instance has been set up successfully and has established a connection with Bitbucket, the process of creating indexes has failed. Consequently, search functionality within Bitbucket Data Center remains unavailable.EnvironmentBitbucket Data Center 7.21.x +External OpenSearch instance.DiagnosisThe below error is seen in Bitbucket logs: 023-02-22 15:51:36,119 ERROR [search-indexing:thread-1] c.a.b.i.s.i.e.DefaultIndexEventWorker Indexing - Failed for repository PRJ/repo (id: 285) with error: Indexing for repository with id 285 failed and should be retriedcom.atlassian.bitbucket.internal.search.indexing.exceptions.IndexException: Indexing for repository with id 285 failed and should be retriedat com.atlassian.bitbucket.internal.search.indexing.indexer.DefaultIndexService.lambda$updateIndexStateForError$26(DefaultIndexService.java:457)...Caused by: java.lang.IllegalStateException: Object content expected to have '_type' field, but was not present; present fields: _index, _id, _version, result, _shards, _seq_no, _primary_term, statusat com.atlassian.elasticsearch.client.content.ObjectContent.lambda$getOrThrow$5(ObjectContent.java:110) CauseBased on the error message, it appears that OpenSearch is expecting a specific field named '_type' that is not present in the payload sent by Bitbucket. This results in the java.lang.IllegalStateException and fails the index creation. In summary, it appears that there is an incompatibility issue between the version of OpenSearch being used and Bitbucket.SolutionWe recommend double-checking the supported platforms documentation for the version of Bitbucket that you are currently using. It is essential to ensure that you are using the compatible version of OpenSearch that aligns with the Bitbucket version. If the version is not compatible, we suggest upgrading or reinstalling the appropriate version of OpenSearch on your remote instance and reconnecting it with Bitbucket.If the indexes have been migrated from Elastcisearch to OpenSearch and such issue happened, you can proceed with deleting and rebuilding the search index.

Explore the comprehensive full-text search engine comparison: Manticore Search vs OpenSearch. Discover performance, features, and scalability to determine the ideal solution for your project’s search requirements.OverviewSelecting the right search engine is vital for project success. Compare Manticore Search and OpenSearch, two powerful search engines, to find the perfect match for your high-performance, scalable search needs.By examiningkey features, we can better understand how Manticore Search and OpenSearch compare in varioususe casesand requirements. Let’s delve into the specifics of each engine to help you make an informed decision for your search implementation.What is Manticore SearchManticore Search is an open-source, high-performance search engine designed for full-text search and real-time data indexing. Known for its speed, efficiency, and scalability, it excels in handling large datasets and offers scalability, making it a great choice for applications requiring rapid search responses. With a focus on simplicity, it provides flexible features like advanced filtering, ranking, and querying capabilities, while also being highly customizable.What is OpensearchOpenSearch is an open-source search engine and analytics suite, originally forked from Elasticsearch. Built to remain under the permissive Apache 2.0 license, it focuses on maintaining a fully open-source approach. OpenSearch offers distributed search and analytics, real-time indexing, and is highly scalable. It includes tools like OpenSearch Dashboards and OpenSearch Ingestion for visualizing and ingesting data, making it ideal for log analytics, observability, and search applications. With a community-driven governance model, OpenSearch allows users to retain flexibility without vendor lock-in.Key FeaturesManticore Search and OpenSearch are two powerful full-text search engines that offer robust solutions for document indexing and searching. Each engine brings its unique strengths to the table, providing developers with tools to create fast and efficient search experiences. Let’s explore the key features of both engines to help you determine which one best fits your project requirements.FeatureManticore SearchOpensearchOpen sourceGPLv3✓Full-text search✓✓Autocomplete (predictive typing suggestions)✓✓Fuzzy search (handling typos)✓✓Vector Search (semantic and similarity-based searching)✓✓Boolean full-text search (AND, OR, NOT query support)✓✓Faceting (organize and narrow search results)✓✓Grouping and aggregation (combine related search results)✓✓Geospatial search (location-based search capabilities)✓✓JOINs (combine data from different sources)✓✗Synonyms (support for alternate search terms)✓✓Percolate search (match queries to incoming data)✓✓Real-time indexing (immediate document updates)✓⚠️ (not by default)Secondary indexes (support multiple indexes for faster queries)✓✓Row-wise storage (row-oriented data storage)✓✗Columnar storage (column-oriented data storage)✓✓Docstore (store original values)✓✓Cost-based query optimizer (choose the best query plan based on data)✓✓In-place updates (update documents without re-indexing)✓✗Nested object/JSON field (support complex JSON structures)✓✓Auto-schema (automatic schema generation for data)✓✓SQL support (query using SQL syntax)✓⚠️ (very limited)JSON support (query using JSON syntax)✓✓Bulk inserts (insert large amounts of data efficiently)✓✓Distributed search (search across multiple nodes)✓✓High availability (data mirroring and load balancing)✓✓Replication (copy data across different nodes for redundancy)✓✓Auto-sharding (automatic data partitioning across nodes)⚠️ coming soon🔗✓Authentication (built-in user authentication features)✗✓Both Manticore Search and OpenSearch

Response 200 response Modified application/json content type Modified mysql-settings property Modified log_output property Added GET /dbaas-opensearch/{name} Response 200 response Modified application/json content type Modified opensearch-settings property Modified indices_memory_max_index_buffer_size, search_backpressure, shard_indexing_pressure, knn_memory_circuit_breaker_enabled, indices_memory_min_index_buffer_size, knn_memory_circuit_breaker_limit properties Added GET /dbaas-postgres/{name} Response 200 response Modified application/json content type Modified pgbouncer-settings property Modified max_prepared_statements property Added POST /dbaas-grafana/{name} Body application/json content type Modified grafana-settings property Modified wal, custom_domain properties Added POST /dbaas-mysql/{name} Body application/json content type Modified mysql-settings property Modified log_output property Added POST /dbaas-opensearch/{name} Body application/json content type Modified opensearch-settings property Modified indices_memory_max_index_buffer_size, search_backpressure, shard_indexing_pressure, knn_memory_circuit_breaker_enabled, indices_memory_min_index_buffer_size, knn_memory_circuit_breaker_limit properties Added POST /dbaas-postgres/{name} Body application/json content type Modified pgbouncer-settings property Modified max_prepared_statements property Added PUT /dbaas-external-endpoint-datadog/{endpoint-id} Body application/json content type Modified settings property Modified datadog-api-key property Modified Property is now required Breaking PUT /dbaas-grafana/{name} Body application/json content type Modified grafana-settings property Modified wal, custom_domain properties Added PUT /dbaas-mysql/{name} Body application/json content type Modified mysql-settings property Modified log_output property Added PUT /dbaas-opensearch/{name} Body application/json content type Modified opensearch-settings property Modified indices_memory_max_index_buffer_size, search_backpressure, shard_indexing_pressure, knn_memory_circuit_breaker_enabled, indices_memory_min_index_buffer_size, knn_memory_circuit_breaker_limit properties Added PUT /dbaas-postgres/{name} Body application/json content type Modified pgbouncer-settings property Modified max_prepared_statements property Added Oct 23, 2024 Change #6f50b6bc 2.0.0 Compare Show more 2 structure changes including: 2 Modifications GET /dbaas-service-type Response 200 response Modified application/json content type Modified dbaas-service-types property Modified plans property Modified GET /dbaas-service-type/{service-type-name} Response 200 response Modified application/json content type Modified plans property Modified family, zones properties Added Oct 22, 2024 Change #abc1fa64 Compare Show more 2 structure changes including: 2 Modifications GET /dbaas-service-type Response