DBMS > IBM Db2 warehouse vs. Snowflake vs. SQream DB vs. Tarantool vs. YDB

System Properties Comparison IBM Db2 warehouse vs. Snowflake vs. SQream DB vs. Tarantool vs. YDB

Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

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

a GPU-based, columnar RDBMS for big data analytics workloads

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Document store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

www.ibm.com/products/db2/warehouse

www.snowflake.com

sqream.com

www.tarantool.io

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

docs.snowflake.net/manuals/index.html

docs.sqream.com

www.tarantool.io/en/doc

ydb.tech/en/docs

Developer

IBM

Snowflake Computing Inc.

SQream Technologies

Yandex

Initial release

2014

2017

2008

2019

Current release

2022.1.6, December 2022

2.10.0, May 2022

License

Commercial or Open Source

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

Open Source

Apache 2.0; commercial license available

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++, CUDA, Haskell, Java, Scala

C and C++

Server operating systems

hosted

Linux

BSD
Linux
macOS

Linux

Data scheme

yes

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

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

string, double, decimal, uuid, integer, blob, boolean, datetime

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

SQL-like query language (YQL)

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

Open binary protocol

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

PL/SQL, SQL PL

user defined functions

user defined functions in Python

Lua, C and SQL stored procedures

Triggers

yes

similar concept for controling cloud resources

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal and vertical partitioning

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

fine grained access rights according to SQL-standard

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

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

Access rights defined for Yandex Cloud users

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