DBMS > Hive vs. KeyDB vs. Lovefield vs. NSDb

System Properties Comparison Hive vs. KeyDB vs. Lovefield vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Embeddable relational database for web apps written in pure JavaScript

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

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

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

hive.apache.org

github.com/Snapchat/KeyDB
keydb.dev

google.github.io/lovefield

nsdb.io

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

docs.keydb.dev

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

nsdb.io/Architecture

Developer

Apache Software Foundation

initially developed by Facebook

EQ Alpha Technology Ltd.

Google

Initial release

2012

2019

2014

2017

Current release

3.1.3, April 2022

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSD-3

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

JavaScript

Java, Scala

Server operating systems

All OS with a Java VM

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

yes: int, bigint, decimal, string

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.

Secondary indexes

yes

by using the Redis Search module

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

JDBC
ODBC
Thrift

Proprietary protocol

RESP - REdis Serialization Protoco

gRPC
HTTP REST
WebSocket

Supported programming languages

C++
Java
PHP
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript

Java
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Lua

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Using Apache Lucene

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, groups and roles

simple password-based access control and ACL

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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