DBMS > CrateDB vs. InfluxDB vs. MongoDB vs. ScyllaDB
System Properties Comparison CrateDB vs. InfluxDB vs. MongoDB vs. ScyllaDB
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Name | CrateDB Xexclude from comparison | InfluxDB Xexclude from comparison | MongoDB Xexclude from comparison | ScyllaDB Xexclude from comparison | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Distributed Database based on Lucene | DBMS for storing time series, events and metrics | One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure | Cassandra and DynamoDB compatible wide column store | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Spatial DBMS Search engine Time Series DBMS Vector DBMS | Time Series DBMS | Document store | Wide column store | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Relational DBMS | Spatial DBMS with GEO package | Spatial DBMS Search engine integrated Lucene index, currently in MongoDB Atlas only. Time Series DBMS Time Series Collections introduced in Release 5.0 Vector DBMS currently available in the MongoDB Atlas cloud service only | Key-value store | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cratedb.com | www.influxdata.com/products/influxdb-overview | www.mongodb.com | www.scylladb.com | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cratedb.com/docs | docs.influxdata.com/influxdb | www.mongodb.com/docs/manual | docs.scylladb.com | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Crate | MongoDB, Inc | ScyllaDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2013 | 2013 | 2009 | 2015 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 2.7.6, April 2024 | 6.0.7, June 2023 | ScyllaDB Open Source 5.4.1, January 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source | Open Source MIT-License; commercial enterprise version available | Open Source MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available. | Open Source Open Source (AGPL), commercial license available | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no MongoDB available as DBaaS (MongoDB Atlas) | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform. |
| Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | Go | C++ | C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support | Linux OS X through Homebrew | Linux OS X Solaris Windows | Linux | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | Flexible Schema (defined schema, partial schema, schema free) | schema-free | schema-free Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema. | schema-free | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | Numeric data and Strings | yes string, integer, double, decimal, boolean, date, object_id, geospatial | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | yes | yes cluster global secondary indices | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes, but no triggers and constraints, and PostgreSQL compatibility | SQL-like query language | Read-only SQL queries via the MongoDB Atlas SQL Interface | SQL-like DML and DDL statements (CQL) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC ODBC PostgreSQL wire protocol Prometheus Remote Read/Write RESTful HTTP API | HTTP API JSON over UDP | GraphQL HTTP REST Prisma proprietary protocol using JSON | Proprietary protocol (CQL) compatible with CQL (Cassandra Query Language, an SQL-like language) RESTful HTTP API (DynamoDB compatible) Thrift | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .NET Erlang Go community maintained client Java JavaScript (Node.js) community maintained client Perl community maintained client PHP Python R Ruby community maintained client Scala community maintained client | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | Actionscript unofficial driver C C# C++ Clojure unofficial driver ColdFusion unofficial driver D unofficial driver Dart unofficial driver Delphi unofficial driver Erlang Go Groovy unofficial driver Haskell Java JavaScript Kotlin Lisp unofficial driver Lua unofficial driver MatLab unofficial driver Perl PHP PowerShell unofficial driver Prolog unofficial driver Python R unofficial driver Ruby Rust Scala Smalltalk unofficial driver Swift | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions (Javascript) | no | JavaScript | yes, Lua | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | yes in MongoDB Atlas only | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding in enterprise version only | Sharding Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime. | Sharding | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Configurable replication on table/partition-level | selectable replication factor in enterprise version only | Multi-Source deployments with MongoDB Atlas Global Clusters Source-replica replication | selectable replication factor Representation of geographical distribution of servers is possible | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Read-after-write consistency on record level | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour | Eventual Consistency Tunable Consistency can be individually decided for each write operation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no typically not used, however similar functionality with DBRef possible | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no unique row identifiers can be used for implementing an optimistic concurrency control strategy | no | Multi-document ACID Transactions with snapshot isolation | no Atomicity and isolation are supported for single operations | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes optional, enabled by default | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes Depending on used storage engine | yes In-memory storage engine introduced with MongoDB version 3.2 | yes in-memory tables | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | rights management via user accounts | simple rights management via user accounts | Access rights for users and roles | Access rights for users can be defined per object | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CrateDB | InfluxDB | MongoDB | ScyllaDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | The enterprise database for time series, documents, and vectors. Distributed - Native... » more | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | MongoDB provides an integrated suite of cloud database and data services to accelerate... » more | ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling... » more | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | Built around the flexible document data model and unified API, MongoDB is a developer... » more | Highly-performant (efficiently utilizes full resources of a node and network; millions... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics... » more | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of... » more | ScyllaDB is ideal for applications that require high throughput and low latency at... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Across all continents, CrateDB is used by companies of all sizes to meet the most... » more | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,... » more | Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®... » more | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month... » more | ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | See CrateDB pricing > » more | Open source core with closed source clustering available either on-premise or on... » more | MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses... » more | ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based... » 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Related products and services | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3rd parties | Navicat for MongoDB gives you a highly effective GUI interface for MongoDB database management, administration and development. » more CData: Connect to Big Data & NoSQL through standard Drivers. » more Studio 3T: The world's favorite IDE for working with MongoDB » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CrateDB | InfluxDB | MongoDB | ScyllaDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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? | Snowflake is the DBMS of the Year 2021 PostgreSQL is the DBMS of the Year 2020 PostgreSQL is the DBMS of the Year 2018 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT CrateDB Announces Availability of CrateDB on Google Cloud Marketplace How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things Crate.io Expands CrateDB Cloud with the Launch of CrateDB Edge Crate.io Introduces CrateDB 2.0 Enterprise and Open Source Editions provided by Google News | Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services 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 | Why MongoDB Plunged Over 35% in May MongoDB First Quarter 2025 Earnings: Beats Expectations Looking Into MongoDB's Recent Short Interest - MongoDB (NASDAQ:MDB) Should You Buy MongoDB, Snowflake, and Atlassian at Their 52-Week Lows? Why MongoDB Plunged Over 35% in May 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 Running ScyllaDB NoSQL on Kubernetes with Spot Instances ScyllaDB on AWS is a NoSQL Database Built for Gigabyte-to-Petabyte Scale | Amazon Web Services ScyllaDB Database Review | eWeek provided by Google News |
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