DBMS > Apache IoTDB vs. Cassandra vs. Datastax Enterprise vs. InfluxDB vs. YugabyteDB
System Properties Comparison Apache IoTDB vs. Cassandra vs. Datastax Enterprise vs. InfluxDB vs. YugabyteDB
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Name | Apache IoTDB Xexclude from comparison | Cassandra Xexclude from comparison | Datastax Enterprise Xexclude from comparison | InfluxDB Xexclude from comparison | YugabyteDB Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink | Wide-column store based on ideas of BigTable and DynamoDB Optimized for write access | 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. | DBMS for storing time series, events and metrics | High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Time Series DBMS | Wide column store | Wide column store | Time Series DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Vector DBMS starting with release V5 | Document store Graph DBMS Spatial DBMS Search engine Vector DBMS | Spatial DBMS with GEO package | Document store Wide column store | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | iotdb.apache.org | cassandra.apache.org | www.datastax.com/products/datastax-enterprise | www.influxdata.com/products/influxdb-overview | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html | cassandra.apache.org/doc/latest | docs.datastax.com | docs.influxdata.com/influxdb | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation | Apache Software Foundation Apache top level project, originally developped by Facebook | DataStax | Yugabyte Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2018 | 2008 | 2011 | 2013 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 1.1.0, April 2023 | 4.1.3, July 2023 | 6.8, April 2020 | 2.7.6, April 2024 | 2.19, September 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2.0 | Open Source Apache version 2 | commercial | Open Source MIT-License; commercial enterprise version available | 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. | Astra DB: Multi-cloud DBaaS built on Apache Cassandra. | 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. | 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 | Java | Java | Go | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All OS with a Java VM (>= 1.8) | BSD Linux OS X Windows | Linux OS X | Linux OS X through Homebrew | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free | schema-free | schema-free | depending on used data model | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | Numeric data and Strings | 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 | yes | restricted only equality queries, not always the best performing solution | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like query language | SQL-like SELECT, DML and DDL statements (CQL) | SQL-like DML and DDL statements (CQL); Spark SQL | SQL-like query language | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC Native API | Proprietary protocol CQL (Cassandra Query Language, an SQL-like language) Thrift | Proprietary protocol CQL (Cassandra Query Language) TinkerPop Gremlin with DSE Graph | HTTP API JSON over UDP | 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++ Go Java Python Scala | C# C++ Clojure Erlang Go Haskell Java JavaScript Node.js Perl PHP Python Ruby Scala | C C# C++ Java JavaScript (Node.js) PHP Python Ruby | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | C C# C++ Go Java JavaScript (Node.js) PHP Python Ruby Rust Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | no | no | no | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning (by time range) + vertical partitioning (by deviceId) | Sharding no "single point of failure" | Sharding no "single point of failure" | Sharding in enterprise version only | Hash and Range Sharding, row-level geo-partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas | selectable replication factor Representation of geographical distribution of servers is possible | configurable replication factor, datacenter aware, advanced replication for edge computing | selectable replication factor in enterprise version only | Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | Integration with Hadoop and Spark | yes | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Strong Consistency with Raft | Eventual Consistency Immediate Consistency can be individually decided for each write operation | Immediate Consistency Tunable Consistency consistency level can be individually decided with each write operation | Strong consistency on writes and tunable consistency on reads | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | no Atomicity and isolation are supported for single operations | no Atomicity and isolation are supported for single operations | no | 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 | no | yes | yes Depending on used storage engine | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | yes | Access rights for users can be defined per object | Access rights for users can be defined per object | simple rights management via user accounts | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Apache IoTDB | Cassandra | Datastax Enterprise | InfluxDB | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Apache Cassandra is the leading NoSQL, distributed database management system, well... » more | DataStax Enterprise is scale-out data infrastructure for enterprises that need to... » more | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | YugabyteDB is an open source distributed SQL database for cloud native transactional... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | No single point of failure ensures 100% availability . Operational simplicity for... » more | Supporting the following application requirements: Zero downtime - Built on Apache... » more | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS.... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Internet of Things (IOT), fraud detection applications, recommendation engines, product... » more | Applications that must be massively and linearly scalable with 100% uptime and able... » more | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | Systems of record and engagement for cloud native applications that require resilience,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best... » more | Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and... » more | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Cassandra is used by 40% of the Fortune 100. » more | Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top... » 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 | Apache license Pricing for commercial distributions provided by DataStax and available... » more | Annual subscription » more | Open source core with closed source clustering available either on-premise or on... » more | Apache 2.0 license for the database » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | An Introduction to David Jones-Gilardi, Developer Relations Introducing Tejas Kumar, Developer Relations Engineer Indexing All of Wikipedia on a Laptop An Introduction to Phil Nash, Developer Relations Focus on Creativity, Not Clusters: DataStax Mission Control in Action! | Apache Superset and InfluxDB Cloud 3.0 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Apache IoTDB | Cassandra | Datastax Enterprise | InfluxDB | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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