DBMS > EJDB vs. etcd vs. EventStoreDB vs. SAP SQL Anywhere vs. Yaacomo

System Properties Comparison EJDB vs. etcd vs. EventStoreDB vs. SAP SQL Anywhere vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A distributed reliable key-value store

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

github.com/Softmotions/ejdb

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

www.eventstore.com

www.sap.com/products/technology-platform/sql-anywhere.html

yaacomo.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

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

developers.eventstore.com

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Softmotions

Event Store Limited

SAP

formerly Sybase

Q2WEB GmbH

Initial release

2012

1992

2009

Current release

3.4, August 2019

21.2, February 2021

17, July 2015

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2.0

Open Source

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

Server operating systems

server-less

FreeBSD
Linux
Windows

experimental

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Android
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library

gRPC
JSON over HTTP

ADO.NET
HTTP API
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

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

Server-side scripts

Stored procedures

yes, in C/C++, Java, .Net or Perl

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Source-replica replication

Database mirroring

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

fine grained access rights according to SQL-standard

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