DBMS > Lovefield vs. Snowflake vs. Tarantool vs. TDSQL for MySQL

System Properties Comparison Lovefield vs. Snowflake vs. Tarantool vs. TDSQL for MySQL

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

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

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

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

Document store
Spatial DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Website

google.github.io/lovefield

www.snowflake.com

www.tarantool.io

www.tencentcloud.com/products/dcdb

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.snowflake.net/manuals/index.html

www.tarantool.io/en/doc

www.tencentcloud.com/document/product/1042

Developer

Google

Snowflake Computing Inc.

Tencent

Initial release

2014

2008

2013

Current release

2.1.12, February 2017

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

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

commercial

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

JavaScript

C and C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

BSD
Linux
macOS

hosted

Data scheme

yes

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

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

yes

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

Full-featured ANSI SQL support

yes

APIs and other access methods

CLI Client
JDBC
ODBC

Open binary protocol

JDBC
ODBC

Supported programming languages

JavaScript

JavaScript (Node.js)
Python

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

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Lua, C and SQL stored procedures

yes

Triggers

Using read-only observers

similar concept for controling cloud resources

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

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

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

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

Multi-source replication
Source-replica 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, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes, full featured in-memory storage engine with persistence

User concepts

Access control

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

Users with fine-grained authorization concept

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