DBMS > Amazon Neptune vs. GridDB vs. InfluxDB vs. Memgraph vs. Vertica
System Properties Comparison Amazon Neptune vs. GridDB vs. InfluxDB vs. Memgraph vs. Vertica
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Name | Amazon Neptune Xexclude from comparison | GridDB Xexclude from comparison | InfluxDB Xexclude from comparison | Memgraph Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Fast, reliable graph database built for the cloud | Scalable in-memory time series database optimized for IoT and Big Data | DBMS for storing time series, events and metrics | An open source graph database built for real-time streaming and compatible with Neo4j | Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Graph DBMS RDF store | Time Series DBMS | Time Series DBMS | Graph DBMS | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Key-value store Relational DBMS | Spatial DBMS with GEO package | Spatial DBMS Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/neptune | griddb.net | www.influxdata.com/products/influxdb-overview | memgraph.com | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | aws.amazon.com/neptune/developer-resources | docs.griddb.net | docs.influxdata.com/influxdb | memgraph.com/docs | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Social network pages | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Toshiba Corporation | Memgraph Ltd | OpenText previously Micro Focus and Hewlett Packard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2017 | 2013 | 2013 | 2017 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 5.1, August 2022 | 2.7.5, January 2024 | 12.0.3, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | Open Source AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available | Open Source MIT-License; commercial enterprise version available | commercial Free license available | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C++ | Go | C and C++ | C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Linux | Linux OS X through Homebrew | Linux | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes | schema-free | schema-free and schema-optional | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes numerical, string, blob, geometry, boolean, timestamp | Numeric data and Strings | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | no | yes | no | No Indexes Required. Different internal optimization strategy, but same functionality included. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | SQL92, SQL-like TQL (Toshiba Query Language) | SQL-like query language | no | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | OpenCypher RDF 1.1 / SPARQL 1.1 TinkerPop Gremlin | JDBC ODBC Proprietary protocol RESTful HTTP/JSON API | HTTP API JSON over UDP | Bolt protocol Cypher query language | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# Go Java JavaScript PHP Python Ruby Scala | C C++ Go Java JavaScript (Node.js) Perl PHP Python Ruby | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | .Net C C++ Elixir Go Haskell Java JavaScript PHP Python Ruby Scala | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | no | no | yes, PostgreSQL PL/pgSQL, with minor differences | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | no | yes, called Custom Alerts | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none | Sharding | Sharding in enterprise version only | Sharding dynamic graph partitioning | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances. | Source-replica replication | selectable replication factor in enterprise version only | Multi-source replication using RAFT | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs | no | no | no Bi-directional Spark integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate consistency within container, eventual consistency across containers | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes Relationships in graphs | no | no | yes relationships in graphs | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID at container level | no | ACID with snapshot isolation | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes, multi-version concurrency control (MVCC) | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes with encyption-at-rest | yes | yes | yes with periodic snapshot and write-ahead logging (WAL) of changes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes Depending on used storage engine | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | Access rights for users can be defined per database | simple rights management via user accounts | Users, roles and permissions | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon Neptune | GridDB | InfluxDB | Memgraph | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | GridDB is a highly scalable, in-memory time series database optimized for IoT and... » more | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | Memgraph directly connects to your streaming infrastructure so you and your team... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | 1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model... » more | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | Business Source License ensures a future for the Memgraph community MAGE algorithm... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system. » more | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | Graph algorithms in bioinformatics Social network analysis Cryptocurrency network... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki... » more | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | GitHub trending repository » more | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Open Source license (AGPL v3 & Apache v2) Commercial license (subscription) » more | Open source core with closed source clustering available either on-premise or on... » more | You can check out our pricing model and licenses on the company website . » more | Cost-based models and subscription-based models are both available. One license is... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Sync Data from InfluxDB v2 to v3 With the Quix Template Infrastructure Monitoring Basics: Getting Started with Telegraf, InfluxDB, and Grafana Comparing Dates in Java: A Tutorial Python ARIMA Tutorial Time Series, InfluxDB, and Vector Databases | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon Neptune | GridDB | InfluxDB | Memgraph | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Why Build a Time Series Data Platform? Time Series DBMS are the database category with the fastest increase in popularity Time Series DBMS as a new trend? | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Uncover hidden connections in unstructured financial data with Amazon Bedrock and Amazon Neptune | Amazon Web ... Analyze large amounts of graph data to get insights and find trends with Amazon Neptune Analytics | Amazon Web ... Create a Virtual Knowledge Graph with Amazon Neptune and an Amazon S3 data lake | Amazon Web Services Visualize and explore knowledge graphs quickly by connecting metaphactory to Amazon Neptune | Amazon Web ... Improve availability of Amazon Neptune during engine upgrade using blue/green deployment | Amazon Web Services provided by Google News | General Availability of GridDB® 5.5 Enterprise Edition ~Enhancing the efficiency of IoT system development and ... General Availability of GridDB 5.3 Enterprise Edition ~ Major Enhancement in IoT and Time Series Data Analysis ... Toshiba launches cloudy managed IoT database service running its own GridDB Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ... General Availability of GridDB 5.1 Enterprise Edition ~ Continuous database usage in the event of data center failure ... provided by Google News | Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services Amazon Timestream: Managed InfluxDB for Time Series Data AWS and InfluxData partner to offer managed time series database Timestream for InfluxDB How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World provided by Google News | Graph database company Memgraph raises $9.34M Graph Database Market to grow at a CAGR of 19.9% from 2022 to 2027|Increased demand for low-latency queries is a ... Modeling and Navigating a Transportation Network with Memgraph London-based Memgraph raises over €8 million in seed funding to provide Streaming Graph Algorithms to the masses Making Your Own Memory Graph To Detect Memory Issues On iOS provided by Google News | OCI Object Storage Completes Technical Validation of Vertica in Eon Mode Solving Big Data Challenges with Data Science at Uber Vertica by OpenText and Anritsu Sign New Deal for Next-Gen Architecture and 5G Network Capabilities Stonebraker Seeks to Invert the Computing Paradigm with DBOS OpenText expands enterprise portfolio with AI and Micro Focus integrations provided by Google News |
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