DBMS > Manticore Search vs. Oracle Berkeley DB vs. Stardog vs. Warp 10

System Properties Comparison Manticore Search vs. Oracle Berkeley DB vs. Stardog vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

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

Widely used in-process key-value store

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Search engine

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Graph DBMS
RDF store

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	0.29
Rank	#302	Overall
	#21	Search engines

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

manticoresearch.com

www.oracle.com/database/technologies/related/berkeleydb.html

www.stardog.com

www.warp10.io

Technical documentation

manual.manticoresearch.com

docs.oracle.com/cd/E17076_05/html/index.html

docs.stardog.com

www.warp10.io/content/02_Getting_started

Developer

Manticore Software

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Stardog-Union

SenX

Initial release

2017

1994

2010

2015

Current release

6.0, February 2023

18.1.40, May 2020

7.3.0, May 2020

License

Commercial or Open Source

Open Source

GPL version 2

Open Source

commercial license available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

Apache License 2.0

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, Java, C++ (depending on the Berkeley DB edition)

Java

Server operating systems

FreeBSD
Linux
macOS
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

Fixed schema

schema-free

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

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

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.

Can index from XML

yes

only with the Berkeley DB XML edition

Import/export of XML data possible

Secondary indexes

yes

full-text index on all search fields

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

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

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

HTTP API
Jupyter
WebSocket

Supported programming languages

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

yes

WarpScript

Triggers

yes

only for the SQL API

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

Source-replica replication

Multi-source replication in HA-Cluster

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in HA-Cluster

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights for users and roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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