DBMS > Neo4j vs. Redis vs. ScyllaDB vs. Tarantool vs. Vertica
System Properties Comparison Neo4j vs. Redis vs. ScyllaDB vs. Tarantool vs. Vertica
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Name | Neo4j Xexclude from comparison | Redis Xexclude from comparison | ScyllaDB Xexclude from comparison | Tarantool Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings | Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies. | Cassandra and DynamoDB compatible wide column store | In-memory computing platform with a flexible data schema for efficiently building high-performance applications | 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 | Key-value store Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence | Wide column store | Document store Key-value store Relational DBMS | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store with RedisJSON Graph DBMS with RedisGraph Spatial DBMS Search engine with RediSearch Time Series DBMS with RedisTimeSeries Vector DBMS | Key-value store | Spatial DBMS with Tarantool/GIS extension | Spatial DBMS Time Series DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | neo4j.com | redis.com redis.io | www.scylladb.com | www.tarantool.io | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | neo4j.com/docs | docs.redis.com/latest/index.html redis.io/docs | docs.scylladb.com | www.tarantool.io/en/doc | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Neo4j, Inc. | Redis project core team, inspired by Salvatore Sanfilippo Development sponsored by Redis Inc. | ScyllaDB | VK | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2007 | 2009 | 2015 | 2008 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 5.20, May 2024 | 7.2.5, May 2024 | ScyllaDB Open Source 5.4.1, January 2024 | 2.10.0, May 2022 | 12.0.3, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source GPL version3, commercial licenses available | Open Source source-available extensions (modules), commercial licenses for Redis Enterprise | Open Source Open Source (AGPL), commercial license available | Open Source BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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. | Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs. | Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java, Scala | C | C++ | C and C++ | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux Can also be used server-less as embedded Java database. OS X Solaris Windows | BSD Linux OS X Windows ported and maintained by Microsoft Open Technologies, Inc. | Linux | BSD Linux macOS | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free and schema-optional | schema-free | schema-free | Flexible data schema: relational definition for tables with ability to store json-like documents in columns | 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 | partial Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes | yes | string, double, decimal, uuid, integer, blob, boolean, datetime | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes pluggable indexing subsystem, by default Apache Lucene | yes with RediSearch module | yes cluster global secondary indices | yes | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | with RediSQL module | SQL-like DML and DDL statements (CQL) | Full-featured ANSI SQL support | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Bolt protocol Cypher query language Java API Neo4j-OGM Object Graph Mapper RESTful HTTP API Spring Data Neo4j TinkerPop 3 | proprietary protocol RESP - REdis Serialization Protocol | Proprietary protocol (CQL) compatible with CQL (Cassandra Query Language, an SQL-like language) RESTful HTTP API (DynamoDB compatible) Thrift | Open binary protocol | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net Clojure Elixir Go Groovy Haskell Java JavaScript Perl PHP Python Ruby Scala | C C# C++ Clojure Crystal D Dart Elixir Erlang Fancy Go Haskell Haxe Java JavaScript (Node.js) Lisp Lua MatLab Objective-C OCaml Pascal Perl PHP Prolog Pure Data Python R Rebol Ruby Rust Scala Scheme Smalltalk Swift Tcl Visual Basic | For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby | C C# C++ Erlang Go Java JavaScript Lua Perl PHP Python Rust | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes User defined Procedures and Functions | Lua; Redis Functions coming in Redis 7 (slides and Github) | yes, Lua | Lua, C and SQL stored procedures | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes via event handler | publish/subscribe channels provide some trigger functionality; RedisGears | no | yes, before/after data modification events, on replication events, client session events | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | yes using Neo4j Fabric | Sharding Automatic hash-based sharding with support for hash-tags for manual sharding | Sharding | Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime. | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Causal Clustering using Raft protocol available in in Enterprise Version only | Multi-source replication with Redis Enterprise Pack Source-replica replication Chained replication is supported | selectable replication factor Representation of geographical distribution of servers is possible | Asynchronous replication with multi-master option Configurable replication topology (full-mesh, chain, star) Synchronous quorum replication (with 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 | through RedisGears | no | no Bi-directional Spark integration | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Causal and Eventual Consistency configurable in Causal Cluster setup Immediate Consistency in stand-alone mode | Eventual Consistency Causal consistency can be enabled in Active-Active databases Strong consistency with Redis Raft Strong eventual consistency with Active-Active | Eventual Consistency Tunable Consistency can be individually decided for each write operation | Casual consistency across sharding partitions Eventual consistency within replicaset partition when using asyncronous replication Immediate Consistency within single instance Sequential consistency including linearizable read within replicaset partition when using Raft | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes Relationships in graphs | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | Atomic execution of command blocks and scripts and optimistic locking | no Atomicity and isolation are supported for single operations | ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes Data access is serialized by the server | yes | yes, cooperative multitasking | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes Configurable mechanisms for persistency via snapshots and/or operations logs | yes | yes, write ahead logging | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes in-memory tables | yes, full featured in-memory storage engine with persistence | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | Access Control Lists (ACLs): redis.io/docs/management/security/acl LDAP and Role-Based Access Control (RBAC) for Redis Enterprise Mutual TLS authentication: redis.io/docs/management/security/encryption Password-based authentication | Access rights for users can be defined per object | Access Control Lists Mutual TLS authentication for Tarantol Enterprise Password based authentication Role-based access control (RBAC) and LDAP for Tarantol Enterprise Users and Roles | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Neo4j | Redis | ScyllaDB | Tarantool | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Neo4j is the market leader, graph database category creator, and the most widely... » more | Highly-performant (efficiently utilizes full resources of a node and network; millions... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | ScyllaDB is ideal for applications that require high throughput and low latency at... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,... » more | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » more | ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based... » more | Cost-based models and subscription-based models are both available. One license is... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Neo4j-Databricks Connector Delivers Deeper Insights, Faster GenAI Development This Week in Neo4j: Podcast, Testing, Knowledge Graph, GenAI and more Neo4j and Snowflake Bring Graph Data Science Into the AI Data Cloud RDF vs. Property Graphs: Choosing the Right Approach for Implementing a Knowledge Graph This Week in Neo4j: Importing Data, NODES, GenAI, Going Meta and more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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3rd parties | Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.
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Neo4j | Redis | ScyllaDB | Tarantool | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | PostgreSQL is the DBMS of the Year 2018 MySQL, PostgreSQL and Redis are the winners of the March ranking MongoDB is the DBMS of the year, defending the title from last year | Data processing speed and reliability: in-memory synchronous replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Neo4j employs knowledge graphs as part of the AI stack Neo4j graph analytics integrated with Snowflake's AI cloud – Blocks and Files Neo4j Announces Collaboration with Microsoft to Advance GenAI and Data Solutions USA - English - India - English Using Neo4j’s graph database for AI in Azure Neo4j announces collaboration with Snowflake for advanced AI insights and predictive analytics – Intelligent CIO North ... provided by Google News | Redis moves to source-available licenses Redis switches licenses, acquires Speedb to go beyond its core in-memory database Redis expands data management capabilities with Speedb acquisition – Blocks and Files In-memory database Redis wants to dabble in disk Redis acquires storage engine startup Speedb to enhance its open-source database provided by Google News | Sleeping at Scale - Delivering 10k Timers per Second per Node with Rust, Tokio, Kafka, and Scylla ScyllaDB Raises $43M to Take on MongoDB at Scale, Push Database Performance to New Levels ScyllaDB on AWS is a NoSQL Database Built for Gigabyte-to-Petabyte Scale | Amazon Web Services ScyllaDB Database Review | eWeek Scylla review: Apache Cassandra supercharged provided by Google News | Tarantool Announces New Enterprise Version With Enhanced Scaling and Monitoring Capabilities Deploying Tarantool Cartridge applications with zero effort (Part 1) VShard — horizontal scaling in Tarantool Accelerating PHP connectors for Tarantool using Async, Swoole, and Parallel provided by Google News | MapR Hadoop Upgrade Runs HP Vertica Stonebraker Seeks to Invert the Computing Paradigm with DBOS OpenText expands enterprise portfolio with AI and Micro Focus integrations Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK | Amazon Web Services Postgres pioneer Michael Stonebraker promises to upend the database once more provided by Google News |
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