DBMS > Drizzle vs. Manticore Search vs. SQLite vs. Stardog vs. Teradata Aster

System Properties Comparison Drizzle vs. Manticore Search vs. SQLite vs. Stardog vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Widely used embeddable, in-process RDBMS

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

manticoresearch.com

www.sqlite.org

www.stardog.com

Technical documentation

manual.manticoresearch.com

www.sqlite.org/docs.html

docs.stardog.com

Developer

Drizzle project, originally started by Brian Aker

Manticore Software

Dwayne Richard Hipp

Stardog-Union

Teradata

Initial release

2008

2017

2000

2010

2005

Current release

7.2.4, September 2012

6.0, February 2023

3.45.3 (15 April 2024), April 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

GPL version 2

Open Source

Public Domain

commercial

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

commercial

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++

Java

Server operating systems

FreeBSD
Linux
OS X

FreeBSD
Linux
macOS
Windows

server-less

Linux
macOS
Windows

Linux

Data scheme

yes

Fixed schema

yes

dynamic column types

schema-free and OWL/RDFS-schema support

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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.

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

Import/export of XML data possible

yes

in Aster File Store

Secondary indexes

yes

full-text index on all search fields

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

SQL-92 is not fully supported

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

yes

APIs and other access methods

JDBC

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C++
Java
PHP

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

R packages

Triggers

hooks for callbacks inside the server can be used.

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Synchronous replication based on Galera library

none

Multi-source replication in HA-Cluster

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in HA-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

relationships in graphs

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles

fine grained access rights according to SQL-standard

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