DBMS > ArangoDB vs. InfluxDB vs. Stardog vs. Vertica vs. YugabyteDB
System Properties Comparison ArangoDB vs. InfluxDB vs. Stardog vs. Vertica vs. YugabyteDB
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | ArangoDB Xexclude from comparison | InfluxDB Xexclude from comparison | Stardog Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | YugabyteDB Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language. | DBMS for storing time series, events and metrics | Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization | 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. | High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Graph DBMS Key-value store Search engine | Time Series DBMS | Graph DBMS RDF store | Relational DBMS Column oriented | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Spatial DBMS with GEO package | Spatial DBMS Time Series DBMS | Document store Wide column store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | arangodb.com | www.influxdata.com/products/influxdb-overview | www.stardog.com | www.vertica.com | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.arangodb.com | docs.influxdata.com/influxdb | docs.stardog.com | vertica.com/documentation | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Developer | ArangoDB Inc. | Stardog-Union | OpenText previously Micro Focus and Hewlett Packard | Yugabyte Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2013 | 2010 | 2005 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 3.11.5, November 2023 | 2.7.6, April 2024 | 7.3.0, May 2020 | 12.0.3, January 2023 | 2.19, September 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2; Commercial license (Enterprise) available | Open Source MIT-License; commercial enterprise version available | commercial 60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students | commercial Limited community edition free | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour. | 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 | C++ | Go | Java | C++ | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Windows | Linux OS X through Homebrew | Linux macOS Windows | Linux | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free automatically recognizes schema within a collection | schema-free | schema-free and OWL/RDFS-schema support | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | depending on used data model | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes string, double, boolean, list, hash | Numeric data and Strings | 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. | no | no Import/export of XML data possible | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | yes supports real-time indexing in full-text and geospatial | No Indexes Required. Different internal optimization strategy, but same functionality included. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | SQL-like query language | Yes, compatible with all major SQL variants through dedicated BI/SQL Server | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | AQL Foxx Framework Graph API (Gremlin) GraphQL query language HTTP API Java & SpringData JSON style queries VelocyPack/VelocyStream | HTTP API JSON over UDP | GraphQL query language HTTP API Jena RDF API OWL RDF4J API Sesame REST HTTP Protocol SNARL SPARQL Spring Data Stardog Studio TinkerPop 3 | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | 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++ Clojure Elixir Go Java JavaScript (Node.js) PHP Python R Rust | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | .Net Clojure Groovy Java JavaScript Python Ruby | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | C C# C++ Go Java JavaScript (Node.js) PHP Python Ruby Rust Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | JavaScript | no | user defined functions and aggregates, HTTP Server extensions in Java | yes, PostgreSQL PL/pgSQL, with minor differences | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | yes via event handlers | yes, called Custom Alerts | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding since version 2.0 | Sharding in enterprise version only | none | horizontal partitioning, hierarchical partitioning | Hash and Range Sharding, row-level geo-partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication with configurable replication factor | selectable replication factor in enterprise version only | Multi-source replication in HA-Cluster | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no can be done with stored procedures in JavaScript | no | no | no Bi-directional Spark integration | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency configurable per collection or per write Immediate Consistency OneShard (highly available, fault-tolerant deployment mode with ACID semantics) | Immediate Consistency in HA-Cluster | Immediate Consistency | Strong consistency on writes and tunable consistency on reads | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes relationships in graphs | no | yes relationships in graphs | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | 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 | 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 Depending on used storage engine | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | yes | simple rights management via user accounts | Access rights for users and roles | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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ArangoDB | InfluxDB | Stardog | Vertica OpenText™ Vertica™ | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Graph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading... » more | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | YugabyteDB is an open source distributed SQL database for cloud native transactional... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Consolidation: As a native multi-model database, can be used as a full blown document... » more | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS.... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Native multi-model in ArangoDB is being used for a broad range of projects across... » more | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | Systems of record and engagement for cloud native applications that require resilience,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Cisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,... » 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 | ArangoDB is the leading native multi-model database with over 11,000 stargazers on... » more | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | 2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Very permissive Apache 2 License for Community Edition & commercial licenses are... » more | Open source core with closed source clustering available either on-premise or on... » more | Cost-based models and subscription-based models are both available. One license is... » more | Apache 2.0 license for the database » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Scaling Data Collection: Solving Renewable Energy Challenges with InfluxDB Deadman Alerts with Grafana and InfluxDB Cloud 3.0 Chasing the Skies: Monitoring Flights with InfluxDB Monitoring Your Cloud Environments and Applications with InfluxDB Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
ArangoDB | InfluxDB | Stardog | Vertica OpenText™ Vertica™ | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | The Weight of Relational Databases: Time for Multi-Model? | 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 | ArangoGraphML: Simplifying the Power of Graph Machine Learning How to Build Knowledge Graph Enhanced Chatbot with ChatGPT and ArangoDB ArangoDB brings yet more money into graph database market with $27.8M round ArangoDB expands scope of graph database platform Open source graph database company ArangoDB raises $27.8M provided by Google News | Amazon Timestream for InfluxDB is now generally available Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB? Amazon Timestream: Managed InfluxDB for Time Series Data InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency 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 Postgres pioneer Michael Stonebraker promises to upend the database once more Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK | Amazon Web Services provided by Google News | Yugabyte Achieves PCI DSS Level 1 Compliance, Validating Secure and Scalable Distributed PostgreSQL for ... YugabyteDB Becomes First Distributed SQL Database Vendor to Complete CIS Benchmark The surprising link between Formula One and enterprise PostgreSQL optimisation Yugabyte Embraces 'No Downtime, No Limits,' as the Theme of the Upcoming Distributed SQL Summit Asia Can Yugabyte Become The Defacto Database For Large-Scale, Cloud Native Applications? provided by Google News |
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