DBMS > eXtremeDB vs. GBase vs. Heroic vs. LevelDB vs. Manticore Search

System Properties Comparison eXtremeDB vs. GBase vs. Heroic vs. LevelDB vs. Manticore Search

Editorial information provided by DB-Engines

Name

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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.

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

www.mcobject.com

www.gbase.cn

github.com/spotify/heroic

github.com/google/leveldb

manticoresearch.com

Technical documentation

www.mcobject.com/docs/extremedb.htm

spotify.github.io/heroic

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

manual.manticoresearch.com

Developer

McObject

General Data Technology Co., Ltd.

Spotify

Google

Manticore Software

Initial release

2001

2004

2014

2011

2017

Current release

8.2, 2021

GBase 8a, GBase 8s, GBase 8c

1.23, February 2021

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD

Open Source

GPL version 2

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 and C++

C, Java, Python

Java

C++

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

Illumos
Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

Data scheme

yes

schema-free

Fixed schema

Typing

predefined data types such as float or date

yes

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

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.

support of XML interfaces available

yes

Can index from XML

Secondary indexes

yes

via Elasticsearch

yes

full-text index on all search fields

SQL

Support of SQL

yes

with the option: eXtremeSQL

Standard with numerous extensions

SQL-like query language

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

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

Supported programming languages

.Net
C
C#
C++
Java
Lua
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

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

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

Sharding

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

none

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

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.

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

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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