DBMS > Datastax Enterprise vs. InfluxDB vs. Milvus vs. Vertica vs. YugabyteDB
System Properties Comparison Datastax Enterprise vs. InfluxDB vs. Milvus vs. Vertica vs. YugabyteDB
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| Name | Datastax Enterprise Xexclude from comparison | InfluxDB Xexclude from comparison | Milvus Xexclude from comparison | Vertica  OpenText™ Vertica™ 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. | DBMS for storing time series, events and metrics | A DBMS designed for efficient storage of vector data and vector similarity searches | 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 | Wide column store | Time Series DBMS | Vector DBMS | Relational DBMS Column oriented | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store Graph DBMS Spatial DBMS Search engine Vector DBMS | Spatial DBMS with GEO package | Spatial DBMS Time Series DBMS | Document store Wide column store | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.datastax.com/products/datastax-enterprise | www.influxdata.com/products/influxdb-overview | milvus.io | www.vertica.com | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.datastax.com | docs.influxdata.com/influxdb | milvus.io/docs/overview.md | vertica.com/documentation | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | DataStax | OpenText previously Micro Focus and Hewlett Packard | Yugabyte Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2011 | 2013 | 2019 | 2005 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 6.8, April 2020 | 2.7.6, April 2024 | 2.4.4, May 2024 | 12.0.3, January 2023 | 2.19, September 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | Open Source MIT-License; commercial enterprise version available | Open Source Apache Version 2.0 | 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. | 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. | Zilliz Cloud – Cloud-native service for Milvus | 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 | Go | C++, Go | C++ | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X | Linux OS X through Homebrew | Linux macOS 10.14 or laterWindows with WSL 2 enabled | Linux | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | schema-free | 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 | Numeric data and Strings | Vector, Numeric and String | 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 | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | no | no | No Indexes Required. Different internal optimization strategy, but same functionality included. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-like DML and DDL statements (CQL); Spark SQL | SQL-like query language | no | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | Proprietary protocol CQL (Cassandra Query Language) TinkerPop Gremlin with DSE Graph | HTTP API JSON over UDP | RESTful HTTP API | 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# 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++ Go Java JavaScript (Node.js) Python | 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 | no | no | no | yes, PostgreSQL PL/pgSQL, with minor differences | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | no | no | yes, called Custom Alerts | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding no "single point of failure" | Sharding in enterprise version only | Sharding | horizontal partitioning, hierarchical partitioning | 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 | selectable replication factor in enterprise version only | 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 | yes | no | no | no Bi-directional Spark integration | 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 | Bounded Staleness Eventual Consistency Immediate Consistency Session Consistency Tunable Consistency | Immediate Consistency | Strong consistency on writes and tunable consistency on reads | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no Atomicity and isolation are supported for single operations | no | no | 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 | yes Depending on used storage engine | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users can be defined per object | simple rights management via user accounts | Role based access control and fine grained access rights | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Datastax Enterprise | InfluxDB | Milvus | Vertica OpenText™ Vertica™ | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | 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 | Milvus is an open-source and cloud-native vector database built for production-ready... » 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 | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | Highly available, versatile, and robust with millisecond latency. Supports batch... » 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 | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | RAG: retrieval augmented generation Video media : video understanding, video deduplication.... » 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 | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | 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 | As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise... » more | 2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Annual subscription » more | Open source core with closed source clustering available either on-premise or on... » more | Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed... » more | Apache 2.0 license for the database » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | Real-Time Visualization for IIoT Data Deploying InfluxDB and Telegraf to Monitor Kubernetes Telegraf 1.32 Release Notes An Introductory Guide to Cloud Security for IIoT Building Real-Time Android Apps with InfluxDB Cloud: Data Logging, Querying, and Visualization | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Datastax Enterprise | InfluxDB | Milvus | Vertica OpenText™ Vertica™ | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | 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? | Vector databases | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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