DBMS > GBase vs. Hazelcast vs. LevelDB vs. Manticore Search vs. SQLite

System Properties Comparison GBase vs. Hazelcast vs. LevelDB vs. Manticore Search vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A widely adopted in-memory data grid

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

Multi-storage database for search, including full-text search.

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.gbase.cn

hazelcast.com

github.com/google/leveldb

manticoresearch.com

www.sqlite.org

Technical documentation

hazelcast.org/imdg/docs

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

manual.manticoresearch.com

www.sqlite.org/docs.html

Developer

General Data Technology Co., Ltd.

Hazelcast

Google

Manticore Software

Dwayne Richard Hipp

Initial release

2004

2008

2011

2017

2000

Current release

GBase 8a, GBase 8s, GBase 8c

5.3.6, November 2023

1.23, February 2021

6.0, February 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

BSD

Open Source

GPL version 2

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, Java, Python

Java

C++

Server operating systems

Linux

All OS with a Java VM

Illumos
Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

server-less

Data scheme

yes

schema-free

Fixed schema

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes

not rigid because of 'dynamic typing' concept.

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

the object must implement a serialization strategy

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions

yes

Event Listeners, Executor Services

user defined functions

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

none

Synchronous replication based on Galera library

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

The original contents of fields are not stored in the Manticore index.

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

yes

Role-based access control

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