DBMS > KeyDB vs. Lovefield vs. NSDb vs. Splunk

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

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Editorial information provided by DB-Engines

Name

Description

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

Analytics Platform for Big Data

Primary database model

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

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

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

github.com/Snapchat/KeyDB
keydb.dev

google.github.io/lovefield

nsdb.io

www.splunk.com

Technical documentation

docs.keydb.dev

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

nsdb.io/Architecture

docs.splunk.com/Documentation/Splunk

Developer

EQ Alpha Technology Ltd.

Google

Splunk Inc.

Initial release

2019

2014

2017

2003

Current release

2.1.12, February 2017

License

Commercial or Open Source

Open Source

BSD-3

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Limited free edition and free developer edition available

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++

JavaScript

Java, Scala

Server operating systems

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

partial

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

yes

yes: int, bigint, decimal, string

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

Secondary indexes

yes

by using the Redis Search module

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

Splunk Search Processing Language for search commands

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

gRPC
HTTP REST
WebSocket

HTTP REST

Supported programming languages

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

yes

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

simple password-based access control and ACL

Access rights for users and roles

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More resources

DB-Engines blog posts

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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Recent citations in the news

Oh, snap! Snap snaps up database developer KeyDB
12 May 2022, TechCrunch

Garnet–open-source faster cache-store speeds up applications, services
18 March 2024, Microsoft

Snap Acquires KeyDB for Open-Source Services
17 May 2022, XR Today

Dragonfly 1.0 Released For What Claims To Be The World's Fastest In-Memory Data Store
20 March 2023, Phoronix

Microsoft open-sources Garnet cache-store -- a Redis rival?
19 March 2024, The Stack

provided by Google News

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