DBMS > AlaSQL vs. DolphinDB vs. H2 vs. HarperDB vs. KeyDB

System Properties Comparison AlaSQL vs. DolphinDB vs. H2 vs. HarperDB vs. KeyDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Primary database model

Document store
Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Website

github.com/Snapchat/KeyDB
keydb.dev

Technical documentation

github.com/AlaSQL/alasql

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

www.h2database.com/html/main.html

docs.harperdb.io/docs

docs.keydb.dev

Developer

Andrey Gershun & Mathias R. Wulff

DolphinDB, Inc

Thomas Mueller

HarperDB

EQ Alpha Technology Ltd.

Initial release

2014

2018

2005

2017

2019

Current release

v2.00.4, January 2022

2.2.220, July 2023

3.1, August 2021

License

Commercial or Open Source

Open Source

MIT-License

commercial

free community version available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

free community edition available

Open Source

BSD-3

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

JavaScript

C++

Java

Node.js

C++

Server operating systems

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

Linux
Windows

All OS with a Java VM

Linux
OS X

Linux

Data scheme

schema-free

yes

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

partial

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

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.

Secondary indexes

yes

by using the Redis Search module

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like query language

yes

SQL-like data manipulation statements

APIs and other access methods

JavaScript API

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

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

JavaScript

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

Java

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

Custom Functions

since release 3.1

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

the nodes on which a table resides can be defined

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

none

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

yes

ACID

Atomic execution of specific operations

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

yes, using LMDB

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

fine grained access rights according to SQL-standard

Access rights for users and roles

simple password-based access control and ACL

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