DBMS > Axibase vs. DolphinDB vs. KeyDB vs. STSdb

System Properties Comparison Axibase vs. DolphinDB vs. KeyDB vs. STSdb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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.

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Time Series DBMS

Time Series DBMS
Vector DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

axibase.com/docs/atsd/finance

www.dolphindb.com

github.com/Snapchat/KeyDB
keydb.dev

github.com/STSSoft/STSdb4

Technical documentation

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

docs.keydb.dev

Developer

Axibase Corporation

DolphinDB, Inc

EQ Alpha Technology Ltd.

STS Soft SC

Initial release

2013

2018

2019

2011

Current release

15585

v2.00.4, January 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

free community version available

Open Source

BSD-3

Open Source

GPLv2, commercial license available

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

Java

C++

Server operating systems

Linux

Linux
Windows

Linux

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

partial

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

yes

primitive types and user defined types (classes)

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

SQL-like query language

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

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

Proprietary protocol

RESP - REdis Serialization Protoco

.NET Client API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

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

C#
Java

Server-side scripts

Stored procedures

yes

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

none

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
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

Transaction concepts

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

yes

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

simple password-based access control and ACL

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

The Ultimate ATV Test: Suzuki’s King Quad 750 AXI Rugged Package vs. Alaska’s Hunting Season
14 October 2020, Outdoor Life

provided by Google News

Snap snaps up database developer KeyDB to make its infrastructure more snappy
12 May 2022, TechCrunch

Introducing Garnet – an open-source, next-generation, faster cache-store for accelerating applications and services
18 March 2024, Microsoft

Microsoft open-sources unique “Garnet” cache-store; a Redis rival?
19 March 2024, The Stack

Dragonfly 0.13 Database Adds Experimental SSD-Based Data Tiering, More SIMD Work
2 January 2023, Phoronix

Beyond the mainstream database offerings
26 March 2020, TechCentral.ie

provided by Google News

Share this page