ナレッジグラフ市場 – 2030年までの世界予測

出版社 MarketsandMarkets
出版年月 2025年1月

Knowledge Graph Market – Global Forecast to 2030

ナレッジグラフ市場 – ソリューション (エンタープライズナレッジグラフプラットフォーム、グラフデータベースエンジン、ナレッジマネジメントツールセット)、モデル タイプ [リソース記述フレームワーク (RDF) トリプルストア、ラベル付きプロパティグラフ] – 2030年までの世界予測
Knowledge Graph Market by Solution (Enterprise Knowledge Graph Platform, Graph Database Engine, Knowledge Management Toolset), Model Type (Resource Description Framework (RDF) Triple Stores, Labeled Property Graph) – Global Forecast to 2030

The construction of intelligent knowledge graphs through AI is expected to change how organizations deal with large datasets. The effort of human intervention is drastically reduced when it comes to identifying and extricating relationships between different data points. The automation includes the processes carried out by most types of AI-driven tools such as natural language processing (NLP), machine learning algorithms, etc., to automatically interpret, unstructured or structured data, identify relevant patterns, and correlate such relevant information. This automation speeds up the construction of the graphs and at the same time increases accuracy, ensuring that the relationships represented in it are as relevant and up to date as possible to an end user.

AI によるインテリジェントなナレッジ グラフの構築により、組織が大規模なデータセットを扱う方法が変わると予想されます。異なるデータポイント間の関係を特定して抽出する場合、人的介入の労力が大幅に軽減されます。自動化には、自然言語処理 (NLP) や機械学習アルゴリズムなど、ほとんどのタイプの AI 駆動ツールによって実行されるプロセスが含まれており、非構造化データまたは構造化データを自動的に解釈し、関連するパターンを特定し、関連情報を関連付けます。この自動化により、グラフの構築が高速化されると同時に精度が向上し、グラフ内で表される関係がエンド ユーザーにとって可能な限り関連性があり、最新のものになることが保証されます。

ナレッジグラフ市場 – 2030年までの世界予測
knowledge-graph-market-ecosystem

The major players in the Knowledge Graph market include IBM Corporation (US), Oracle (US), Microsoft Corporation (US), AWS (US), Neo4j (US), Progress Software (US), TigerGraph (US), Stardog (US), Franz Inc (US), Ontotext (Bulgaria), Openlink Software (US), Graphwise (US), Altair (US), Bitnine ( South Korea) ArangoDB (US),  Fluree (US), Memgraph (UK), Datavid (UK), and SAP (Germany), GraphBase (Australia), Metaphacts (Germany), Relational AI (US), Wisecube (US), Smabbler (Poland), Onlim (Austria), Graphaware (UK), Diffbot (US), Eccenca (Germany), Conversight (US), , Semantic Web Company (Austria), ESRI (US). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches, enhancements, and acquisitions to expand their Knowledge Graph market footprint.

The report provides insights on the following pointers:

Analysis of key drivers (rising demand for AI/generative AI solutions, rapid growth in data volume and complexity, growing demand for semantic search), restraints (data quality and Integration challenges, scalability Issues) opportunities (data unification and rapid proliferation of knowledge graphs, increasing adoption in healthcare and life sciences), and challenges (lack of expertise and awareness, standardization and interoperability) influencing the growth of the Knowledge Graph market.

  • Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the Knowledge Graph market.
  • Market Development: The report provides comprehensive information about lucrative markets and analyses the Knowledge Graph market across various regions.
  • Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the Knowledge Graph market.

Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading include include IBM Corporation (US), Oracle (US), Microsoft Corporation (US), AWS (US), Neo4j (US), Progress Software (US), TigerGraph (US), Stardog (US), Franz Inc (US), Ontotext (Bulgaria), Openlink Software (US), Graphwise (US), Altair (US), Bitnine ( South Korea) ArangoDB (US),  Fluree (US), Memgraph (UK), GraphBase (Australia), Metaphacts (Germany), Relational AI (US), Wisecube (US), Smabbler (Poland), Onlim (Austria), Graphaware (UK), Diffbot (US), Eccenca (Germany), Conversight (US), , Semantic Web Company (Austria), ESRI (US), Datavid (UK), and SAP (Germany).