--- description: Heimdall Dataを実際に使用したユーザーのレビューから、製品の機能や価格、メリットデメリットをご覧いただけます。類似製品との比較も簡単、ぴったりのSaaSが見つかるはず！ image: https://gdm-localsites-assets-gfprod.imgix.net/images/capterra/og_logo-e5a8c001ed0bd1bb922639230fcea71a.png?auto=format%2Cenhance%2Ccompress title: Heimdall Dataとは？ | 機能や料金、導入事例をご紹介【キャプテラ】 --- 現在地表示: [ホーム](/) > [APMツール](/directory/30208/application-performance-management-software/software) > [Heimdall Data](/software/157942/heimdall-data) # Heimdall Data Canonical: https://www.capterra.jp/software/157942/heimdall-data ページ：1 / 2\ 次へ: [次ページ](https://www.capterra.jp/software/157942/heimdall-data?page=2) > Heimdall Proxyは、クエリ・キャッシュと読み取り／書き込みスプリットによりSQLのパフォーマンスを向上させます。アプリケーションの変更は必要ありません。 > > 評価：9人のユーザーによる評価は**4.9/5**。**おすすめ度**で最高の評価。 ----- ## 概要 ### Heimdall Dataの対象ユーザー eコマース、一般向けアプリケーション、データ・ウェアハウス・アプリケーション ## 簡単な統計と評価 | 測定基準 | 評価 | 詳細 | | **総合評価** | **4.9/5** | 9 レビュー | | 使いやすさ | 4.7/5 | レビュー全体に基づく | | カスタマー・サポート | 5.0/5 | レビュー全体に基づく | | 価格の妥当性 | 4.8/5 | レビュー全体に基づく | | 機能 | 4.9/5 | レビュー全体に基づく | | おすすめ率 | 100% | (10/10 おすすめ度) | ## 企業情報 - **キャプテラについて**: Heimdall Data - **設立**: 2015 ## ビジネスコンテキスト - **価格プラン**: $5,000.00 - **価格モデル**: (無料のトライアル) - **対象となる企業**: 51～200, 201～500, 501～1,000, 1,001～5,000, 5,001～10,000, 10,000+ - **デプロイとプラットフォーム**: クラウド、SaaS、ウェブベース, Linux（オンプレミス） - **サポートされる言語**: 繁体中国語, 英語 - **利用可能な国**: アメリカ合衆国, アルゼンチン, イギリス, カナダ, メキシコ, 中国, 台湾, 日本, 韓国 ## 機能 - グラフィカル・ユーザーインタフェース - サーバモニタリング - デバッグ - データベース変換 - 互換性テスト - 根本原因解析 - 統合型開発環境 - 複数プログラミング言語をサポート ## 統合 (合計16件) - AWS CloudFormation - Amazon Aurora - Amazon RDS - Amazon Redshift - Boost Engagement - Google Cloud - GridGain - Hazelcast - IBM Db2 - MariaDB - Microsoft Azure - Microsoft SQL Server - MySQL - PostgreSQL - Redis Enterprise ... さらに1件の統合 ## サポートのオプション - メール/ヘルプデスク - ナレッジベース - 電話サポート - 24時間対応（オペレータ） ## Category - [APMツール](https://www.capterra.jp/directory/30208/application-performance-management-software/software) ## 関連カテゴリー - [APMツール](https://www.capterra.jp/directory/30208/application-performance-management-software/software) - [データベースソフト](https://www.capterra.jp/directory/18/database-management/software) - [アプリ開発ツール](https://www.capterra.jp/directory/30082/application-development/software) ## 代替製品 1. [Microsoft SQL Server](https://www.capterra.jp/software/1417/sql-server) — 4.6/5 (1974 reviews) 2. [MySQL](https://www.capterra.jp/software/11482/mysql) — 4.6/5 (2094 reviews) 3. [Google Cloud](https://www.capterra.jp/software/170983/google-cloud-platform) — 4.7/5 (2262 reviews) 4. [Airtable](https://www.capterra.jp/software/146652/airtable) — 4.6/5 (2222 reviews) 5. [Oracle Database](https://www.capterra.jp/software/5938/oracle-database) — 4.6/5 (471 reviews) ## レビュー ### "Heimdall for Improved App Speed" — 4.0/5 > **Craig** | *2019年1月15日* | インターネット | おすすめ評価：10.0/10 > > **良いポイント**: Heimdall is easy to set up and get running. Within minutes we had it up and we were testing it with various aspects of our application. The support team was available to us through the entire process, helping us work through what is a unique use case related to how we are using the caching. The support engineer was responsive via email and phone, and worked through various scenarios with us. Super easy install on AWS, which was important to us at the moment. However, installation on Google Cloud is a breeze as well. Heimdall is very flexible. We don't send all of our writes through Heimdall in certain situations, so we had to come up with a more creative way to invalidate the cache. We were able to do that with API calls to Heimdall one one case, and using ruels in another. > > **改善点**: The documentation is largely very good, but there were a few places where we would get confused and need to ask for clarification. It was difficult for us to see the invalidation occurring through the API unless we had the logging turned extremely high, which in turn made it difficult to find the invalidation occurrences That said, we were able to determine is was working with some log spelunking and good testing. > > We implemented Heimdall primarily as a caching layer in front of both a standard PostgreSQL datastore as well as an Apache HAWQ datastore. It was very easy to get set up and get started. It was reasonably well integrated with AWS which made the initial configuration much easier. This was a very easy way for us to get started testing Heimdall on something more than a local database. ----- ### "Insightful visibility into Wirespeed Database interactions" — 5.0/5 > **Ken** | *2017年2月7日* | 航空会社/航空産業 | おすすめ評価：10.0/10 > > **良いポイント**: Visibility Ability to Optimize DB Traffic > > **改善点**: Moderate Learning Curve during initial deployment. > > It was a pleasure to find Heimdall Data and work with their team on several projects. The Heimdall Data Access Platform was the only solution I found for monitoring and evaluating database traffic that was occurring in volumes of 1GB per five minute period. Through use of this tool, I found a vendors defect and pointed to previously unknown and unquantified performance degradations that were periodic. I would recommend this for any database-dependent application because of this visibility. Heimdall Data through optimizations can also remedy peculiarities of a production application or CoS software package that a vendor may be slow to patch. My initial PoC with Heimdall found and documented within a week, persistent and elusive application issues that I had spent months collecting packets for analysis in Riverbed tools. With the packet captures the volume of data was too large and made it impossible to perform troubleshooting of sporadic events. The aggravation and hassle of packet analysis was quite frustrating, I literally lost whole weekends fighting to import packets with out Riverbed crashing. In contrast, The Heimdall Data install was painless on the App server, requiring only a simple configuration and was collecting data immediately on the wire. There was no modification of the Database server required. A good point to note as many DBAs are quite reluctant to install agents on DB servers as a matter of course. Within the week, in consultation with Heimdall Data the anomalies and performance degradations were pinpointed. It was a pleasure working with the whole team and their insight and ability to provide assistance pushed the PoC through to a documented success. I would recommend Heimdall Data to anyone troubleshooting sporadic and performance issues - the icing on the cake is that Heimdall Data can optimize the database traffic as well, and this is a serious issue to consider when dealing with closed source or complex schema. I believe that where Heimdall Data shines is the support they perform in a PoC the expertise they bring to the table is phenomenal and this is why I must give the tool four stars. I think the customer service and rapid turn around that I saw in the PoC demonstrated significant time saved. While you may be able to get up to speed in a year and be prepared to deploy future applications on your own, I would ask for a Professional Services quote first as they are quite efficient and can save you time. ----- ### "Great product with awesome support" — 5.0/5 > **Nate** | *2019年2月12日* | アパレル、ファッション | おすすめ評価：9.0/10 > > **良いポイント**: Heimdall Data is a database load distribution, caching, failover and high availability solution. I have worked with two other companies that offered a subset of this functionality over the past 7 years. There are very few solutions on the market because this is a very complex problem to tackle. What I liked most about the software was probably it's ability to achieve all of these functions within a single product. It's caching ability is unlike any other product I have seen. It's quite good at load distribution and automatic failover. It also has a decentralized model for the traffic routing, which can be good especially in cases where there is concern about a centralized bottleneck in the traffic flow (and/or CPU requirements for SQL routing) > > **改善点**: Ease of configuration could be improved, manually setting up the rules to do read/write split for example (while easy to do if you have the documentation) could be better handled with simple toggles for most use cases(example). The decentralized model has advantages over a centralized model for scalability especially for more distributed applications (e.g. micro services). The previous solutions I used were centralized only. The drawback to decentralized is it can consume quite a bit more resources depending on the number of app servers that you have since you are literally running multiple copies of the software one per application server. > > The problem we are trying to solve is providing means for intelligent automatic failover for database server clusters. At the same time it is great to have the performance enhancing features such as intelligent read/write splits caching. Support has been oustanding. Heimdall data, like the solutions before it was not 100% trouble free to setup. The difference with Heimdall though was the quality and responsiveness of the support. I got support turnarounds in hours or even less with at least info on what the problem is if not communication that they understood the issue and will have a fix for it soon. Compare to a (worst case) scenario with a previous vendor where it literally took more than two years to get resolution on one SQL distribution problem. ----- ### "Heimdall Data's SQL works as advertised quickly providing SQL acceleration on our app." — 5.0/5 > **Paul** | *2017年11月6日* | おすすめ評価：10.0/10 > > **良いポイント**: Heimdall Data's SQL caching software was easy to install and provided an immediate increase in performance. Their analytic tools gave us insight what was really happening with our queries allowing us to optimize our code. Once optimized, not only was the raw SQL faster but the number of cache hits increased giving us even more performance. If you are serious about performance, you need to start with Heimdall. > > **改善点**: Heimdall is not magic. As I mentioned, part of the problem was with the way that our SQL queries were being made. Heimdall did the caching immediately, but we needed to then use the analytics tools to figure out how to further optimize our code. Once we did that, our cache hits went up and we got even more performance. > > Performance plus insight into how to get even more performance. This has allowed us to better satisfy our app customers while cutting the cost of resources. ----- ### "Great Software/Easy to implement/Huge performance boost with no code changes" — 5.0/5 > **Spencer** | *2020年1月21日* | 高等教育 | おすすめ評価：10.0/10 > > **良いポイント**: Easy to configure for read/write splitting, caching, database scaling. Caching has provided a large performance boost without code changes. > > **改善点**: For a small scientific grant funded website the price was a little steep but we were looking to improve performance and decided it was worth it so development time could be spent elsewhere. It has been well worth the price for the improved performance beyond throwing higher performance EC2 instances at the problem. > > We moved a small genomics Java based website to AWS and wanted to implement SQL caching and Read/Write splitting for the database that we had migrated to Aurora MySQL Compatible. Heimdall Data allowed us to do both with no code changes in an afternoon and our overall page loading performance improved 93% over a 2 week testing period. Support reached out during our trial and provided very useful guidance on how best to implement a solution that would work for us. Great software and great support that has allowed us to improve performance and focus on developing new features not changes to support caching and read/write splitting. ----- ページ：1 / 2\ 次へ: [次ページ](https://www.capterra.jp/software/157942/heimdall-data?page=2) ## リンク - [Capterraで表示する](https://www.capterra.jp/software/157942/heimdall-data) ## このページは以下の言語で利用できます | ロケール | URL | | de | | | de-AT | | | de-CH | | | en | | | en-AE | | | en-AU | | | en-CA | | | en-GB | | | en-IE | | | en-IL | | | en-IN | | | en-NZ | | | en-SG | | | en-ZA | | | fr | | | fr-BE | | | fr-CA | | | fr-LU | | | ja | | ----- ## 構造化データ