DBMS > Sequoiadb vs. SingleStore vs. Snowflake vs. Warp 10

System Properties Comparison Sequoiadb vs. SingleStore vs. Snowflake vs. Warp 10

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

NewSQL database with distributed OLTP and SQL

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

Cloud-based data warehousing service for structured and semi-structured data

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

Technical documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.singlestore.com

docs.snowflake.net/manuals/index.html

www.warp10.io/content/02_Getting_started

Developer

Sequoiadb Ltd.

SingleStore Inc.

Snowflake Computing Inc.

SenX

Initial release

2013

2014

2015

Current release

8.5, January 2024

License

Commercial or Open Source

Open Source

Server: AGPL; Client: Apache V2

commercial

free developer edition available

commercial

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C++, Go

Java

Server operating systems

Linux

64 bit version required

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

but no triggers and foreign keys

yes

APIs and other access methods

proprietary protocol using JSON

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

CLI Client
JDBC
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
C++
Java
PHP
Python

Bash
C
C#
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

JavaScript

yes

user defined functions

yes

WarpScript

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

hash partitioning

yes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

yes

selectable replication factor

based on HBase

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

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

Document is locked during a transaction

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

In-memory capabilities

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

yes

User concepts

Access control

simple password-based access control

Fine grained access control via users, groups and roles

Users with fine-grained authorization concept, user roles and pluggable authentication

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

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.