DBMS > DolphinDB vs. Oracle NoSQL vs. Solr vs. SQLite

System Properties Comparison DolphinDB vs. Oracle NoSQL vs. Solr vs. SQLite

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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.

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A widely used distributed, scalable search engine based on Apache Lucene

Widely used embeddable, in-process RDBMS

Primary database model

Time Series DBMS

Document store
Key-value store
Relational DBMS

Search engine

Relational DBMS

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	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.dolphindb.com

www.oracle.com/database/nosql/technologies/nosql

solr.apache.org

www.sqlite.org

Technical documentation

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

solr.apache.org/resources.html

www.sqlite.org/docs.html

Developer

DolphinDB, Inc

Oracle

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2018

2011

2006

2000

Current release

v2.00.4, January 2022

24.1, May 2024

9.6.1, May 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Apache Version 2

Open Source

Public Domain

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++

Java

Server operating systems

Linux
Windows

Linux
Solaris SPARC/x86

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

server-less

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

dynamic column types

Typing

predefined data types such as float or date

yes

optional

yes

supports customizable data types and automatic typing

yes

not rigid because of 'dynamic typing' concept.

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 search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

Solr Parallel SQL Interface

yes

SQL-92 is not fully supported

APIs and other access methods

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

RESTful HTTP API

Java API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Java plugins

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

configurable

ACID within a storage node (=shard)

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

off heap cache

yes

User concepts

Access control

Administrators, Users, Groups

Access rights for users and roles

yes

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