DBMS > DolphinDB vs. jBASE vs. LMDB vs. Microsoft SQL Server vs. Riak KV

System Properties Comparison DolphinDB vs. jBASE vs. LMDB vs. Microsoft SQL Server vs. Riak KV

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 robust multi-value DBMS comprising development tools and middleware

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

Microsofts flagship relational DBMS

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

www.dolphindb.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

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

www.microsoft.com/en-us/sql-server

Technical documentation

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

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.lmdb.tech/doc

learn.microsoft.com/en-US/sql/sql-server

www.tiot.jp/riak-docs/riak/kv/latest

Developer

DolphinDB, Inc

Rocket Software (formerly Zumasys)

Symas

Microsoft

OpenSource, formerly Basho Technologies

Initial release

2018

1991

2011

1989

2009

Current release

v2.00.4, January 2022

5.7

0.9.32, January 2024

SQL Server 2022, November 2022

3.2.0, December 2022

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

commercial

restricted free version is available

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++

Erlang

Server operating systems

Linux
Windows

AIX
Linux
Windows

Linux
Unix
Windows

Linux
Windows

Linux
OS X

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

restricted

SQL

Support of SQL

SQL-like query language

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API
Native Erlang Interface

Supported programming languages

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

.Net
Basic
Jabbascript
Java

.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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, but depending on the SQL-Server Edition

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

User concepts

Access control

Administrators, Users, Groups

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

yes, using Riak Security

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