DBMS > Lovefield vs. Manticore Search vs. Spark SQL vs. Valentina Server

System Properties Comparison Lovefield vs. Manticore Search vs. Spark SQL vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Object-relational database and reports server

Primary database model

Relational DBMS

Search engine

Relational 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	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

google.github.io/lovefield

manticoresearch.com

spark.apache.org/sql

www.valentina-db.net

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

manual.manticoresearch.com

spark.apache.org/docs/latest/sql-programming-guide.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Google

Manticore Software

Apache Software Foundation

Paradigma Software

Initial release

2014

2017

2014

1999

Current release

2.1.12, February 2017

6.0, February 2023

3.5.0 ( 2.13), September 2023

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2

Open Source

Apache 2.0

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

JavaScript

C++

Scala

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

Fixed schema

yes

Typing

predefined data types such as float or date

yes

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

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

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

JDBC
ODBC

ODBC

Supported programming languages

JavaScript

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

Java
Python
R
Scala

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication based on Galera library

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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