DBMS > DolphinDB vs. Lovefield vs. Microsoft Azure Cosmos DB vs. Splunk vs. Tkrzw

System Properties Comparison DolphinDB vs. Lovefield vs. Microsoft Azure Cosmos DB vs. Splunk vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Embeddable relational database for web apps written in pure JavaScript

Globally distributed, horizontally scalable, multi-model database service

Analytics Platform for Big Data

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Key-value store

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

www.dolphindb.com

google.github.io/lovefield

azure.microsoft.com/services/cosmos-db

www.splunk.com

dbmx.net/tkrzw

Technical documentation

docs.dolphindb.cn/en/help200/index.html

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

learn.microsoft.com/azure/cosmos-db

docs.splunk.com/Documentation/Splunk

Developer

DolphinDB, Inc

Google

Microsoft

Splunk Inc.

Mikio Hirabayashi

Initial release

2018

2014

2003

2020

Current release

v2.00.4, January 2022

2.1.12, February 2017

0.9.3, August 2020

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

Open Source

Apache Version 2.0

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

C++

JavaScript

C++

Server operating systems

Linux
Windows

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

tested with Chrome, Firefox, IE, Safari

hosted

Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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 properties auto-indexed by default

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

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

JavaScript

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
Java
JavaScript
PHP
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

JavaScript

yes

Triggers

Using read-only observers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Implicit feature of the cloud service

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

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

using specific database classes

User concepts

Access control

Administrators, Users, Groups

Access rights can be defined down to the item level

Access rights for users and roles

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