DBMS > Datastax Enterprise vs. Faircom DB vs. Neo4j vs. TimescaleDB vs. YugabyteDB
System Properties Comparison Datastax Enterprise vs. Faircom DB vs. Neo4j vs. TimescaleDB vs. YugabyteDB
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| Name | Datastax Enterprise Xexclude from comparison | Faircom DB  formerly c-treeACE Xexclude from comparison | Neo4j Xexclude from comparison | TimescaleDB Xexclude from comparison | YugabyteDB Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform. | Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs. | Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings | A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL | High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Wide column store | Key-value store Relational DBMS | Graph DBMS | Time Series DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store Graph DBMS Spatial DBMS Search engine Vector DBMS | Relational DBMS | Document store Wide column store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.datastax.com/products/datastax-enterprise | www.faircom.com/products/faircom-db | neo4j.com | www.timescale.com | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.datastax.com | docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html | neo4j.com/docs | docs.timescale.com | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | DataStax | FairCom Corporation | Neo4j, Inc. | Timescale | Yugabyte Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2011 | 1979 | 2007 | 2017 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 6.8, April 2020 | V13, July 2024 | 5.23, August 2024 | 2.15.0, May 2024 | 2.19, September 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | commercial Restricted, free version available | Open Source GPL version3, commercial licenses available | Open Source Apache 2.0 | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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. | Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing. | Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers. | YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | Java | ANSI C, C++ | Java, Scala | C | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X | AIX FreeBSD HP-UX Linux NetBSD OS X QNX SCO Solaris VxWorks Windows easily portable to other OSs | Linux Can also be used server-less as embedded Java database. OS X Solaris Windows | Linux OS X Windows | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | schema free, schema optional, schema required, partial schema, | schema-free and schema-optional | yes | depending on used data model | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes, ANSI SQL Types, JSON, typed binary structures | yes | numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types | 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 | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes pluggable indexing subsystem, by default Apache Lucene | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-like DML and DDL statements (CQL); Spark SQL | yes, ANSI SQL with proprietary extensions | no | yes full PostgreSQL SQL syntax | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | Proprietary protocol CQL (Cassandra Query Language) TinkerPop Gremlin with DSE Graph | ADO.NET Direct SQL JDBC JPA ODBC RESTful HTTP/JSON API RESTful MQTT/JSON API RPC | Bolt protocol Cypher query language Java API Neo4j-OGM Object Graph MapperRESTful HTTP API Spring Data Neo4j TinkerPop 3 | ADO.NET JDBC native C library ODBC streaming API for large objects | JDBC YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C C# C++ Java JavaScript (Node.js) PHP Python Ruby | .Net C C# C++ Java JavaScript (Node.js and browser) PHP Python Visual Basic | .Net Clojure Elixir Go Groovy Haskell Java JavaScript Perl PHP Python Ruby Scala | .Net C C++ Delphi Java JDBCJavaScript Perl PHP Python R Ruby Scheme Tcl | C C# C++ Go Java JavaScript (Node.js) PHP Python Ruby Rust Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | yes .Net, JavaScript, C/C++ | yes User defined Procedures and Functions | user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | yes | yes via event handler | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding no "single point of failure" | File partitioning, horizontal partitioning, sharding Customizable business rules for table partitioning | yes using Neo4j Fabric | yes, across time and space (hash partitioning) attributes | Hash and Range Sharding, row-level geo-partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | configurable replication factor, datacenter aware, advanced replication for edge computing | yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution). | Causal Clustering using Raft protocol available in in Enterprise Version only | Source-replica replication with hot standby and reads on replicas | Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency Tunable Consistency consistency level can be individually decided with each write operation | Eventual Consistency Immediate Consistency Tunable consistency per server, database, table, and transaction | Causal and Eventual Consistency configurable in Causal Cluster setup Immediate Consistency in stand-alone mode | Immediate Consistency | Strong consistency on writes and tunable consistency on reads | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | yes | yes Relationships in graphs | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no Atomicity and isolation are supported for single operations | tunable from ACID to Eventually Consistent | ACID | ACID | Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | Yes, tunable from durable to delayed durability to in-memory | yes | yes | yes based on RocksDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users can be defined per object | Fine grained access rights according to SQL-standard with additional protections for files | Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | fine grained access rights according to SQL-standard | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Datastax Enterprise | Faircom DB formerly c-treeACE | Neo4j | TimescaleDB | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | DataStax Enterprise is scale-out data infrastructure for enterprises that need to... » more | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | YugabyteDB is an open source distributed SQL database for cloud native transactional... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | Supporting the following application requirements: Zero downtime - Built on Apache... » more | Neo4j is the market leader, graph database category creator, and the most widely... » more | PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS.... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | Applications that must be massively and linearly scalable with 100% uptime and able... » more | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | Systems of record and engagement for cloud native applications that require resilience,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and... » more | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top... » more | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » more | 2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Annual subscription » more | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | Apache 2.0 license for the database » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | Elevate Fraud Detection With Neo4j on AWS: Uncover Hidden Patterns and Enhance Accuracy The Ethics of Generative AI: Understanding the Principles and Risks GraphSummit Europe 2024: Actionable Insights From Industry Leaders and Innovators This Week in Neo4j: Knowledge Graph, Data Loading, Olympics, CSV and more Neo4j Expands Cloud Database Capabilities to Power Enterprise-Scale Graph Deployments | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Datastax Enterprise | Faircom DB formerly c-treeACE | Neo4j | TimescaleDB | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Recent citations in the news | DataStax Enterprise 4.0 Gives in-Memory Option to Cassandra DataStax previews new Hyper Converged Data Platform for enterprise AI DataStax to launch AI-integrated data platforms HCDP & DSE 6.9 DataStax Launches New Hyper-Converged Data Platform Giving Enterprises the Complete Modern Data Center Suite Needed for AI in Production DataStax acquires the startup behind low-code AI builder Langflow provided by Google News | FairCom Unveils New Look, FairCom DB v13: Introducing 'DB Made Simple' provided by Google News | Neo4j lowers barriers to graph technology with gen AI copilot, 15x read capacity Implementing GraphReader with Neo4j and LangGraph | by Tomaz Bratanic | Sep, 2024 Neo4j Transforms Its Cloud Database Portfolio to Accelerate Graph Adoption & GenAI for the Enterprise Neo4j eyes GenAI workloads in APAC Neo4j Transforms Its Cloud Database Portfolio to Accelerate Graph Adoption & GenAI for the Enterprise provided by Google News | General availability: Latest version of the TimeScaleDB extension on Azure Database for PostgreSQL - Flexible Server Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers TimescaleDB Is a Vector Database Now, Too PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions Understanding Hyperfunctions in TimescaleDB provided by Google News | YugabyteDB Evolves PostgreSQL to a Distributed Architecture for Modern, Cloud-Native Applications YugabyteDB evolves into a distributed PostgreSQL database for apps that need resilience and scale YugabyteDB 2.19 gets new PostgreSQL-compatibility features YugabyteDB Becomes First Distributed SQL Database Vendor to Complete CIS Benchmark Simplifying cloud-native app development with Yugabyte provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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