MarkLogicは、MarkLogicクラウドサービスにおいてSOC 2 Type II監査を完了し、MarkLogic®データハブサービスがSOC 2 Type IIの5原則（セキュリティ、可用性、処理の整合性、機密性、プライバシー）すべてに準拠していることを証明する報告書を第三者監査機関より受領しました。

エンタープライズデータを管理するための安全でセキュアなプラットフォームを提供することは、複雑化するデータ統合をシンプルにするという、MarkLogicのビジョンにとって非常に重要です。MarkLogicはきめ細かなセキュリティと

We are proud to announce the successful completion of a SOC 2 Type II audit for our cloud service. An independent third party has issued an attestation report for MarkLogic® Data Hub Service on all five SOC 2 Type II principles:  Security, Availability, Processing Integrity, Confidentiality and Privacy.

Providing a safe and secure platform to manage enterprise data is paramount to our vision of simplifying complex data integration. MarkLogic was already the most secure modern database with

With data security, it is important to address the tactical details (think incident patterns, attack vectors, dynamic testing, etc.). But, it’s also important to look at the broader, more strategic issues and concerns with data security.

In talking to many of our customers, we identified three top strategic issues with data security that CIO’s, architects, and business leaders are most concerned about:

Security is getting more and more critical. One recent report from PwC shows the number of security incidents in 2015 increased by 38% compared to 2014. And along with increased risk comes increased spending. According to a recent report by Gartner, worldwide security spending reached $76.9 billion in 2015, and is expected to reach $170 billion by 2020. That’s more than 100 percent growth in just five years.

Needless to say, companies are starting to be more proactive about their approach

Relational databases are designed for either OLTP or OLAP workloads. You can’t use one database for both. Today, that limitation is no longer acceptable as IT struggles to keep pace with the speed of business.

To recap, in previous posts I discussed two aspects of how relational databases have inflexible data models that are not designed for change, are not designed to handle data variety, and are not designed for scale. In this post, I am going to discuss another problem that has