DBMS > ScyllaDB vs. SingleStore vs. XTDB

System Properties Comparison ScyllaDB vs. SingleStore vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Wide column store

Relational DBMS

Document store

Secondary database models

Key-value store

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.scylladb.com

www.singlestore.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.scylladb.com

docs.singlestore.com

www.xtdb.com/docs

Developer

ScyllaDB

SingleStore Inc.

Juxt Ltd.

Initial release

2015

2013

2019

Current release

ScyllaDB Open Source 5.4.1, January 2024

8.5, January 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Open Source (AGPL), commercial license available

commercial

free developer edition available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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

Implementation language

C++

C++, Go

Clojure

Server operating systems

Linux

64 bit version required

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

Secondary indexes

yes

cluster global secondary indices

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL)

yes

but no triggers and foreign keys

limited SQL, making use of Apache Calcite

APIs and other access methods

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

HTTP REST
JDBC

Supported programming languages

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

Clojure
Java

Server-side scripts

Stored procedures

yes, Lua

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

hash partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

in-memory tables

yes

User concepts

Access control

Access rights for users can be defined per object

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
» more

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more

Typical application scenarios

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

Key customers

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

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

Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

F ree Tier and Enterprise Edition
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022, Akmal Chaudhri, SingleStore (sponsor)

Cloud-Based Analytics With SingleStoreDB
9 June 2022, Akmal Chaudhri, SingleStore (sponsor)

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022, Akmal Chaudhri, SingleStore (sponsor)

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Recent citations in the news

Sleeping at Scale - Delivering 10k Timers per Second per Node with Rust, Tokio, Kafka, and Scylla
26 April 2024, InfoQ.com

ScyllaDB Raises $43M to Take on MongoDB at Scale, Push Database Performance to New Levels
17 October 2023, Datanami

ScyllaDB on AWS is a NoSQL Database Built for Gigabyte-to-Petabyte Scale | Amazon Web Services
6 January 2023, AWS Blog

Scylla vs Cassandra: Performance Comparison - DataScienceCentral.com
9 January 2020, Data Science Central

ScyllaDB Database Review | eWeek
21 August 2018, eWeek

provided by Google News

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