DBMS > GridGain vs. Neo4j vs. SingleStore vs. TDengine vs. Virtuoso
System Properties Comparison GridGain vs. Neo4j vs. SingleStore vs. TDengine vs. Virtuoso
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| Name | GridGain Xexclude from comparison | Neo4j Xexclude from comparison | SingleStore  former name was MemSQL Xexclude from comparison | TDengine Xexclude from comparison | Virtuoso Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | GridGain is an in-memory computing platform, built on Apache Ignite | Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | Time Series DBMS and big data platform | Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Key-value store Relational DBMS | Graph DBMS | Relational DBMS | Time Series DBMS | Document store Graph DBMS Native XML DBMS Relational DBMS RDF store Search engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store Spatial DBMS Time Series DBMS Vector DBMS | Relational DBMS | Spatial DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.gridgain.com | neo4j.com | www.singlestore.com | github.com/taosdata/TDengine tdengine.com | virtuoso.openlinksw.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | www.gridgain.com/docs/index.html | neo4j.com/docs | docs.singlestore.com | docs.tdengine.com | docs.openlinksw.com/virtuoso | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | GridGain Systems, Inc. | Neo4j, Inc. | SingleStore Inc. | TDEngine, previously Taos Data | OpenLink Software | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2007 | 2007 | 2013 | 2019 | 1998 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | GridGain 8.5.1 | 5.19, April 2024 | 8.5, January 2024 | 3.0, August 2022 | 7.2.11, September 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | Open Source GPL version3, commercial licenses available | commercial free developer edition available | Open Source AGPL V3, also commercial editions available | Open Source GPLv2, extended commercial license available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers. | SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | Java, C++, .Net | Java, Scala | C++, Go | C | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X Solaris Windows | Linux Can also be used server-less as embedded Java database. OS X Solaris Windows | Linux 64 bit version required | Linux Windows | AIX FreeBSD HP-UX Linux OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | schema-free and schema-optional | yes | yes | yes SQL - Standard relational schema RDF - Quad (S, P, O, G) or Triple (S, P, O) XML - DTD, XML Schema DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | yes | 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. | yes | no | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes pluggable indexing subsystem, by default Apache Lucene | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | ANSI-99 for query and DML statements, subset of DDL | no | yes but no triggers and foreign keys | Standard SQL with extensions for time-series applications | yes SQL-92, SQL-200x, SQL-3, SQLX | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | HDFS API Hibernate JCache JDBC ODBC Proprietary protocol RESTful HTTP API Spring Data | Bolt protocol Cypher query language Java API Neo4j-OGM Object Graph MapperRESTful HTTP API Spring Data Neo4j TinkerPop 3 | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | JDBC RESTful HTTP API | ADO.NET GeoSPARQL HTTP API JDBC Jena RDF API ODBC OLE DB RDF4J API RESTful HTTP API Sesame REST HTTP Protocol SOAP webservices SPARQL 1.1 WebDAV XPath XQuery XSLT | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C# C++ Java PHP Python Ruby Scala | .Net Clojure Elixir Go Groovy Haskell Java JavaScript Perl PHP Python Ruby Scala | Bash C C# Java JavaScript (Node.js) Python | C C# C++ Go Java JavaScript (Node.js) PHP Python Rust | .Net C C# C++ Java JavaScript Perl PHP Python Ruby Visual Basic | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes (compute grid and cache interceptors can be used instead) | yes User defined Procedures and Functions | yes | no | yes Virtuoso PL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes (cache interceptors and events) | yes via event handler | no | yes, via alarm monitoring | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding | yes using Neo4j Fabric | Sharding hash partitioning | Sharding | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | yes (replicated cache) | Causal Clustering using Raft protocol available in in Enterprise Version only | Source-replica replication stores two copies of each physical data partition on two separate nodes | yes | Chain, star, and bi-directional replication Multi-source replication Source-replica replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes (compute grid and hadoop accelerator) | no | no can define user-defined aggregate functions for map-reduce-style calculations | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Causal and Eventual Consistency configurable in Causal Cluster setup Immediate Consistency in stand-alone mode | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | yes Relationships in graphs | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | ACID | ACID | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes, multi-version concurrency control (MVCC) | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Security Hooks for custom implementations | Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | Fine grained access control via users, groups and roles | yes | Fine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| GridGain | Neo4j | SingleStore former name was MemSQL | TDengine | Virtuoso | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | TDengine™ is a next generation data historian purpose-built for Industry 4.0 and... » more | Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | Neo4j is the market leader, graph database category creator, and the most widely... » more | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | High Performance at any Scale: TDengine is purpose-built for handling massive industrial... » more | Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected... » more | Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | Broad use across enterprises and governments including — European Union (EU) US Government... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » more | Customers in various industries worldwide including US and International Industry... » more | TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries... » more | Largest installed-base of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | F ree Tier and Enterprise Edition » more | TDengine OSS is an open source, cloud native time series database. It includes built-in... » more | Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | This Week in Neo4j: Podcast, GraphRAG, GraphQL, Chatbot and more Neo4j Joins the Connect with Confluent Partner Program 10 Inspiring Projects to Spark Your NODES 2024 Presentation New Security Feature in Neo4j Aura: Customer Managed Keys Safeguarding Elections: How Graph Technology Powers Groundbreaking Research on Political Ads | What Is Predictive Maintenance? Can Typical Time-Series Databases Replace Data Historians? TDengine 3.3.0.0 Release Notes How to Unlock Value from Industrial Data with AI and ML Technology Compare InfluxDB vs. TDengine | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| GridGain | Neo4j | SingleStore former name was MemSQL | TDengine | Virtuoso | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Applying Graph Analytics to Game of Thrones MySQL, PostgreSQL and Redis are the winners of the March ranking The openCypher Project: Help Shape the SQL for Graphs | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Recent citations in the news | GridGain's 2023 Growth Positions Company for Strong 2024 GridGain in-memory data and generative AI – Blocks and Files GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024 GridGain to Sponsor and Speak at Three Key Industry Events in May 2024 GridGain Adds Andy Sacks as Chief Revenue Officer, Promotes Lalit Ahuja to Chief Customer and Product Officer ... provided by Google News | Neo4j Announces Collaboration with Microsoft to Advance GenAI and Data Solutions USA - English - India - English Neo4j CTO says new Graph Query Language standard will have 'massive ripple effects' Neo4j Is Planning IPO on Nasdaq, Largest Owner Greenbridge Says Neo4j Empowers Syracuse University with $250K Grant to Tackle Misinformation in 2024 Elections Leveraging Neo4j and Amazon Bedrock for an Explainable, Secure, and Connected Generative AI Solution | Amazon ... provided by Google News | SingleStore CEO sees little future for purpose-built vector databases SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files Announcing watsonx.ai and SingleStore for generative AI applications provided by Google News | TDengine named Top Global Industrial Data Management Solution New TDengine Benchmark Results Show Up to 37.0x Higher Query Performance Than InfluxDB and TimescaleDB Comparing Different Time-Series Databases provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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