DBMS > ArcadeDB vs. LeanXcale vs. openGemini vs. SingleStore

System Properties Comparison ArcadeDB vs. LeanXcale vs. openGemini vs. SingleStore

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Website

arcadedb.com

www.leanxcale.com

www.opengemini.org
github.com/openGemini

www.singlestore.com

Technical documentation

docs.arcadedb.com

docs.opengemini.org/guide

docs.singlestore.com

Developer

Arcade Data

LeanXcale

Huawei and openGemini community

SingleStore Inc.

Initial release

2021

2015

2022

2013

Current release

September 2021

1.1, July 2023

8.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

commercial

free developer edition 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++, Go

Server operating systems

All OS with a Java VM

Linux
Windows

Linux

64 bit version required

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

through Apache Derby

SQL-like query language

yes

but no triggers and foreign keys

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP REST

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

Java

C
Java
Scala

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

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

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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 and common users accounts

Fine grained access control via users, groups and roles

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More resources

DB-Engines blog posts

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022, Akmal Chaudhri, SingleStore (sponsor)

Cloud-Based Analytics With SingleStoreDB
9 June 2022, Akmal Chaudhri, SingleStore (sponsor)

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022, Akmal Chaudhri, SingleStore (sponsor)

show all

Recent citations in the news

Open Source @ Huawei
9 February 2022, Huawei

provided by Google News

SingleStore Partners With Snowflake to Help Users Build Faster, More Efficient Real Time AI Applications
19 September 2024, Business Wire

Third time was the charm for SingleStore in the cloud, CEO says
8 July 2024, The Register

Achieve near real-time analytics on Amazon DynamoDB with SingleStore
16 September 2024, AWS Blog

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

Building a Modern Database: Nikita Shamgunov on Postgres and Beyond
18 April 2024, Madrona Venture Group

provided by Google News

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