DBMS > EJDB vs. Lovefield vs. Manticore Search vs. Rockset vs. VoltDB

System Properties Comparison EJDB vs. Lovefield vs. Manticore Search vs. Rockset vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Embeddable relational database for web apps written in pure JavaScript

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Relational DBMS
Search engine

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

github.com/Softmotions/ejdb

google.github.io/lovefield

manticoresearch.com

rockset.com

www.voltdb.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

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

manual.manticoresearch.com

docs.rockset.com

docs.voltdb.com

Developer

Softmotions

Google

Manticore Software

Rockset

VoltDB Inc.

Initial release

2012

2014

2017

2019

2010

Current release

2.1.12, February 2017

6.0, February 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

GPL version 2

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C++

Java, C++

Server operating systems

server-less

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

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
macOS
Windows

hosted

Linux
OS X

for development

Data scheme

schema-free

yes

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

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

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

full-text index on all search fields

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

Read-only SQL queries, including JOINs

yes

only a subset of SQL 99

APIs and other access methods

in-process shared library

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

HTTP REST

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

JavaScript

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

Go
Java
JavaScript (Node.js)
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Java

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication based on Galera library

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

FOREIGN KEY constraints are not supported

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

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

Access rights for users and organizations can be defined via Rockset console

Users and roles with access to stored procedures

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