Memgraph is an open source graph database built for teams who expect highly performant, advanced analytical insights - as compatible with your current infrastructure as Neo4j (but up to 120x faster).
Never write an overly complex SQL join or query again - making better decisions is easier when you can visualize your problem through an intuitive property graph data model and easily update it any time.
Memgraph allows you to stay agile and confidently add new data to enrich your arsenal without waste or losing important context in the noise.
Leverage Memgraph’s in-memory first storage to accommodate high volumes of streaming data and deliver lightning-fast results for both transactional and analytical workloads. ACID compliant and fully persistent on-disk so you don’t have to worry about losing your data.
Immerse yourself in your data through Memgraph’s ecosystem. Connect to your database instance with a wide range of drivers or WebSocket. There is no need to compromise on your favorite programming language.
- Fortune 500 Chemical Company
Connect to Kafka, Pulsar or Redpanda streams with built-in stream connectors to ingest data and analyze it with a powerful in-memory graph database engine.
Write simple Cypher queries, run a graph algorithm from Memgraph’s open-source MAGE library or write your own modules in C++ or Python.
Traverse the data to find patterns and insights, regardless of the number of necessary hops and visualize the graph in Memgraph Lab.
Memgraph is best suited for use cases with complex data relationships that require real-time processing and high scalability.
Memgraph is designed to be a high-performance graph database, and it typically outperforms many other graph databases in terms of speed and scalability. Key factors contributing to Memgraph's performance are its in-memory architecture and a performant query engine written in C++. Memgraph also offers a variety of tools and features to help optimize query performance, including label and label-property indexes and a custom visualization library. Check our benchmark comparing Memgraph and Neo4j.
When data is stored on disk, the computer has to physically read it from the disk and transfer it to the RAM before it can be processed. This process is relatively slow because it involves several physical processes, such as seeking the right location on the disk and waiting for the data to be read. Writing the data is also much slower for the same reasons.Storing data in the computer's RAM eliminates the need for these physical processes, and data can be accessed and added almost instantly. Therefore, in-memory graph databases are ideal for applications requiring fast data processing, real-time analytics, and quick response times.
Memgraph is an open-source in-memory graph database built for teams that expect highly performant, advanced analytical insights - as compatible with your current infrastructure as Neo4j (but up to 120x faster). Memgraph is powered by a query engine built in C/C++ to handle real-time use cases at an enterprise scale. Memgraph supports strongly-consistent ACID transactions and uses the standardized Cypher query language over Bolt protocol for structuring, manipulating, and exploring data.
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