DBMS > DuckDB vs. Galaxybase vs. Lovefield vs. Tarantool

System Properties Comparison DuckDB vs. Galaxybase vs. Lovefield vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Scalable, ACID-compliant native distributed parallel graph platform

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Document store
Key-value 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	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

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

Website

duckdb.org

galaxybase.com

google.github.io/lovefield

www.tarantool.io

Technical documentation

duckdb.org/docs

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

www.tarantool.io/en/doc

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Google

Initial release

2018

2017

2014

2008

Current release

1.0.0, June 2024

Nov 20, November 2021

2.1.12, February 2017

2.10.0, May 2022

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

Apache 2.0

Open Source

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

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.

Implementation language

C++

C and Java

JavaScript

C and C++

Server operating systems

server-less

Linux

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

tested with Chrome, Firefox, IE, Safari

BSD
Linux
macOS

Data scheme

yes

Strong typed schema

yes

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

Typing

predefined data types such as float or date

yes

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

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

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

Full-featured ANSI SQL support

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

Open binary protocol

Supported programming languages

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

Go
Java
Python

JavaScript

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

Server-side scripts

Stored procedures

user defined procedures and functions

Lua, C and SQL stored procedures

Triggers

Using read-only observers

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

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

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

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes, write ahead logging

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

Role-based access control

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

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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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