DBMS > Amazon DynamoDB vs. InfluxDB vs. ScyllaDB vs. SingleStore vs. YugabyteDB
System Properties Comparison Amazon DynamoDB vs. InfluxDB vs. ScyllaDB vs. SingleStore vs. YugabyteDB
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Name | Amazon DynamoDB Xexclude from comparison | InfluxDB Xexclude from comparison | ScyllaDB Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | YugabyteDB Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Hosted, scalable database service by Amazon with the data stored in Amazons cloud | DBMS for storing time series, events and metrics | Cassandra and DynamoDB compatible wide column store | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Key-value store | Time Series DBMS | Wide column store | Relational DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Spatial DBMS with GEO package | Key-value store | Document store Spatial DBMS Time Series DBMS Vector DBMS | Document store Wide column store | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/dynamodb | www.influxdata.com/products/influxdb-overview | www.scylladb.com | www.singlestore.com | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aws.amazon.com/dynamodb | docs.influxdata.com/influxdb | docs.scylladb.com | docs.singlestore.com | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | ScyllaDB | SingleStore Inc. | Yugabyte Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2013 | 2015 | 2013 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 2.7.6, April 2024 | ScyllaDB Open Source 5.4.1, January 2024 | 8.5, January 2024 | 2.19, September 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial free tier for a limited amount of database operations | Open Source MIT-License; commercial enterprise version available | Open Source Open Source (AGPL), commercial license available | commercial free developer edition available | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS | SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities | 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 | Go | C++ | C++, Go | C and C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Linux OS X through Homebrew | Linux | Linux 64 bit version required | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | schema-free | yes | depending on used data model | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | 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 | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | yes cluster global secondary indices | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | SQL-like query language | SQL-like DML and DDL statements (CQL) | yes but no triggers and foreign keys | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | RESTful HTTP API | HTTP API JSON over UDP | Proprietary protocol (CQL) compatible with CQL (Cassandra Query Language, an SQL-like language) RESTful HTTP API (DynamoDB compatible) Thrift | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | 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 | .Net ColdFusion Erlang Groovy Java JavaScript Perl PHP Python Ruby | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | 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 | Bash C C# Java JavaScript (Node.js) Python | C C# C++ Go Java JavaScript (Node.js) PHP Python Ruby Rust Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | no | yes, Lua | yes | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes by integration with AWS Lambda | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding in enterprise version only | Sharding | Sharding hash partitioning | Hash and Range Sharding, row-level geo-partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes | selectable replication factor in enterprise version only | selectable replication factor Representation of geographical distribution of servers is possible | Source-replica replication stores two copies of each physical data partition on two separate nodes | Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | no | no | no can define user-defined aggregate functions for map-reduce-style calculations | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be specified for read operations | Eventual Consistency Tunable Consistency can be individually decided for each write operation | Immediate Consistency | 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 | ACID ACID across one or more tables within a single AWS account and region | no | no Atomicity and isolation are supported for single operations | ACID | Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes, multi-version concurrency control (MVCC) | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | 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 in-memory tables | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | simple rights management via user accounts | Access rights for users can be defined per object | Fine grained access control via users, groups and roles | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon DynamoDB | InfluxDB | ScyllaDB | SingleStore former name was MemSQL | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted... » more | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | YugabyteDB is an open source distributed SQL database for cloud native transactional... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | Highly-performant (efficiently utilizes full resources of a node and network; millions... » more | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS.... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | ScyllaDB is ideal for applications that require high throughput and low latency at... » more | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | Systems of record and engagement for cloud native applications that require resilience,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,... » more | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput... » more | Customers in various industries worldwide including US and International Industry... » more | 2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Open source core with closed source clustering available either on-premise or on... » more | ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based... » more | F ree Tier and Enterprise Edition » more | Apache 2.0 license for the database » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Efficiency Unleashed: Streamlining Workflows with the InfluxDB Management API What is DevRel at InfluxData An Introductory Guide to Grafana Alerts What to Expect When You’re Expecting InfluxDB: A Guide Introduction to Apache Iceberg | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon DynamoDB | InfluxDB | ScyllaDB | SingleStore former name was MemSQL | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Cloud-based DBMS's popularity grows at high rates The popularity of cloud-based DBMSs has increased tenfold in four years Increased popularity for consuming DBMS services out of the cloud | 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? | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Freecharge lowered their identity management system cost and improved scaling by switching to Amazon DynamoDB ... Migrating Uber's Ledger Data from DynamoDB to LedgerStore Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs Simplify cross-account access control with Amazon DynamoDB using resource-based policies | Amazon Web Services Simplify private connectivity to Amazon DynamoDB with AWS PrivateLink | Amazon Web Services provided by Google News | Introducing Amazon Timestream for InfluxDB: A managed service for the popular open source time-series database ... 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 Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services 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 ScyllaDB on AWS is a NoSQL Database Built for Gigabyte-to-Petabyte Scale | Amazon Web Services ScyllaDB Launches Scylla Cloud Database as a Service Scylla review: Apache Cassandra supercharged provided by Google News | SingleStore CEO sees little future for purpose-built vector databases SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files SingleStore, Snowflake Help Customers Build Enterprise-Ready Generative AI Apps provided by Google News | YugabyteDB Becomes First Distributed SQL Database Vendor to Complete CIS Benchmark Yugabyte Achieves PCI DSS Level 1 Compliance, Validating Secure and Scalable Distributed PostgreSQL for ... Yugabyte Named in the 2023 Gartner® Magic Quadrant™ for Cloud Database Management Systems 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 provided by Google News |
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