DBMS > Datastax Enterprise vs. SingleStore

System Properties Comparison Datastax Enterprise vs. SingleStore

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Our visitors often compare Datastax Enterprise and SingleStore with MongoDB, Apache Cassandra and Redis.

Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

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

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	4.00
Rank	#66	Overall
	#4	Wide column stores

Score	3.69
Rank	#70	Overall
	#37	Relational DBMS

Website

www.datastax.com/products/datastax-enterprise

www.singlestore.com

Technical documentation

docs.datastax.com

docs.singlestore.com

Developer

DataStax

SingleStore Inc.

Initial release

2011

2013

Current release

6.8, April 2020

8.5, January 2024

License

Commercial or Open Source

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

Linux
OS X

Linux

64 bit version required

Data scheme

schema-free

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

SQL-like DML and DDL statements (CQL); Spark SQL

yes

but no triggers and foreign keys

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

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

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

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

Access rights for users can be defined per object

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)

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Recent citations in the news

IBM to acquire DataStax, helping clients bring the power of unstructured data to enterprise AI applications
25 February 2025, IBM

Big Blue To Acquire Datastax in Enterprise AI Play
28 February 2025, Redmond Channel Partner

IBM to Acquire DataStax to Power Generative AI, Tapping into 93% of Enterprise Data
26 February 2025, eWEEK

IBM To Buy DataStax, Expand Watsonx AI Portfolio’s Data Management Capabilities
25 February 2025, CRN Magazine

IBM strengthens AI portfolio with acquisition of DataStax
26 February 2025, techzine.eu

provided by Google News

SingleStore Acquires BryteFlow to Accelerate Adoption of Real-Time Analytics, GenAI
3 October 2024, Business Wire

Announcing watsonx.ai and SingleStore for generative AI applications
16 October 2024, IBM

SingleStore Appoints Nadeem Asghar as Chief Technology Officer
17 April 2025, citybiz

SingleStore acquires BryteFlow to better digest ERP and CRM data
4 October 2024, Blocks and Files

SingleStore's BryteFlow acquisition targets data integration
3 October 2024, TechTarget

provided by Google News

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