DBMS > H2GIS vs. LevelDB vs. SQLite vs. Tarantool vs. Tkrzw

System Properties Comparison H2GIS vs. LevelDB vs. SQLite vs. Tarantool vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Widely used embeddable, in-process RDBMS

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Spatial DBMS

Key-value store

Relational DBMS

Document store
Key-value store
Relational DBMS

Key-value store

Secondary database models

Relational DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.h2gis.org

github.com/google/leveldb

www.sqlite.org

www.tarantool.io

dbmx.net/tkrzw

Technical documentation

www.h2gis.org/docs/home

github.com/google/leveldb/blob/main/doc/index.md

www.sqlite.org/docs.html

www.tarantool.io/en/doc

Developer

CNRS

Google

Dwayne Richard Hipp

Mikio Hirabayashi

Initial release

2013

2011

2000

2008

2020

Current release

1.23, February 2021

3.46.0 (23 May 2024), May 2024

2.10.0, May 2022

0.9.3, August 2020

License

Commercial or Open Source

Open Source

LGPL 3.0

Open Source

BSD

Open Source

Public Domain

Open Source

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

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C and C++

C++

Server operating systems

Illumos
Linux
OS X
Windows

server-less

BSD
Linux
macOS

Linux
macOS

Data scheme

yes

schema-free

yes

dynamic column types

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

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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-92 is not fully supported

Full-featured ANSI SQL support

APIs and other access methods

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Open binary protocol

Supported programming languages

Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

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

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

based on H2

Lua, C and SQL stored procedures

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

none

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

none

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

none

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

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

yes

using specific database classes

User concepts

Access control

yes

based on H2

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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