DBMS > Kinetica vs. LMDB vs. NSDb vs. Splunk vs. TimesTen

System Properties Comparison Kinetica vs. LMDB vs. NSDb vs. Splunk vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

A high performant, light-weight, embedded key-value database library

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

Analytics Platform for Big Data

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.kinetica.com

www.symas.com/symas-embedded-database-lmdb

nsdb.io

www.splunk.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.kinetica.com

www.lmdb.tech/doc

nsdb.io/Architecture

docs.splunk.com/Documentation/Splunk

docs.oracle.com/database/timesten-18.1

Developer

Kinetica

Symas

Splunk Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2011

2017

2003

1998

Current release

7.1, August 2021

0.9.32, January 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Limited free edition and free developer edition available

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

C, C++

Java, Scala

Server operating systems

Linux

Linux
Unix
Windows

Linux
macOS

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

Splunk Search Processing Language for search commands

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

HTTP REST

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

Java
Scala

C#
Java
JavaScript
PHP
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

PL/SQL

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

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