DBMS > etcd vs. EventStoreDB vs. Splice Machine vs. SQream DB

System Properties Comparison etcd vs. EventStoreDB vs. Splice Machine vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Key-value store

Event Store

Relational DBMS

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

etcd.io
github.com/etcd-io/etcd

www.eventstore.com

splicemachine.com

sqream.com

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

developers.eventstore.com

splicemachine.com/how-it-works

docs.sqream.com

Developer

Event Store Limited

Splice Machine

SQream Technologies

Initial release

2012

2014

2017

Current release

3.4, August 2019

21.2, February 2021

3.1, March 2021

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL 3.0, commercial license available

commercial

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++, CUDA, Haskell, Java, Scala

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

APIs and other access methods

gRPC
JSON over HTTP

JDBC
Native Spark Datasource
ODBC

.Net
JDBC
ODBC

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Java

user defined functions in Python

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Shared Nothhing Auto-Sharding, Columnar Partitioning

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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)

yes

Durability

Support for making data persistent

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

Access rights for users, groups and roles according to SQL-standard

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