DBMS > Lovefield vs. Machbase Neo vs. Postgres-XL vs. RocksDB

System Properties Comparison Lovefield vs. Machbase Neo vs. Postgres-XL vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

TimeSeries DBMS for AIoT and BigData

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Website

google.github.io/lovefield

machbase.com

www.postgres-xl.org

rocksdb.org

Technical documentation

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

machbase.com/dbms

www.postgres-xl.org/documentation

github.com/facebook/rocksdb/wiki

Developer

Google

Machbase

Facebook, Inc.

Initial release

2014

2013

2014

since 2012, originally named StormDB

2013

Current release

2.1.12, February 2017

V8.0, August 2023

10 R1, October 2018

9.4.0, June 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free test version available

Open Source

Mozilla public license

Open Source

BSD

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++

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

Linux
macOS

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

C++ API
Java API

Supported programming languages

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

yes

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

In-memory capabilities

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

yes

using MemoryDB

yes

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

fine grained access rights according to SQL-standard

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