DBMS > LeanXcale vs. ReductStore vs. SingleStore vs. Titan

System Properties Comparison LeanXcale vs. ReductStore vs. SingleStore vs. Titan

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Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

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

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Graph 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	0.28
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

www.leanxcale.com

github.com/reductstore
www.reduct.store

www.singlestore.com

github.com/thinkaurelius/titan

Technical documentation

www.reduct.store/docs

docs.singlestore.com

github.com/thinkaurelius/titan/wiki

Developer

LeanXcale

ReductStore LLC

SingleStore Inc.

Aurelius, owned by DataStax

Initial release

2015

2023

2013

2012

Current release

1.9, March 2024

8.5, January 2024

License

Commercial or Open Source

commercial

Open Source

Business Source License 1.1

commercial

free developer edition available

Open Source

Apache license, version 2.0

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++, Rust

C++, Go

Java

Server operating systems

Docker
Linux
macOS
Windows

Linux

64 bit version required

Linux
OS X
Unix
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

yes

through Apache Derby

yes

but no triggers and foreign keys

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
Java
Scala

C++
JavaScript (Node.js)
Python
Rust

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

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

hash partitioning

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

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)

yes

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.

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

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

yes

User concepts

Access control

Fine grained access control via users, groups and roles

User authentification and security via Rexster Graph Server

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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

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

show all

Recent citations in the news

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

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

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

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

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database
24 August 2015, AWS Blog

DataStax acquires Aurelius, the startup behind the Titan graph database
3 February 2015, VentureBeat

DSE Graph review: Graph database does double duty
14 November 2019, InfoWorld

Beyond Titan: The Evolution of DataStax’s New Graph Database
21 June 2016, Datanami

Database Deep Dives: JanusGraph
8 August 2019, IBM

provided by Google News

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