DBMS > AgensGraph vs. etcd vs. Sadas Engine vs. Spark SQL

System Properties Comparison AgensGraph vs. etcd vs. Sadas Engine vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

A distributed reliable key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Graph DBMS
Relational DBMS

Key-value store

Relational DBMS

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

Score	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	7.64
Rank	#54	Overall
	#5	Key-value stores

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Website

bitnine.net/agensgraph

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

www.sadasengine.com

spark.apache.org/sql

Technical documentation

bitnine.net/documentation

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Bitnine Global Inc.

SADAS s.r.l.

Apache Software Foundation

Initial release

2016

2006

2014

Current release

2.1, December 2018

3.4, August 2019

8.0

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

commercial

free trial version available

Open Source

Apache 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++

Scala

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
Windows

experimental

AIX
Linux
Windows

Linux
OS X
Windows

Data scheme

depending on used data model

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

yes

SQL-like DML and DDL statements

APIs and other access methods

Cypher Query Language
JDBC

gRPC
JSON over HTTP

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

horizontal partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

none

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

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Graph DBMS Performance Comparison AgensGraph vs. Neo4j
29 June 2017, Business Wire

Bitnine Releases AgensGraph 2.1, the Multi-model Graph Database Optimized for the Legacy Environment
29 January 2019, Business Wire

provided by Google News

ETCD directives don't go well with RBI's stellar reputation
14 April 2024, Business Standard

Monitor Amazon EKS Control Plane metrics using AWS Open Source monitoring services | Amazon Web Services
12 October 2023, AWS Blog

Killing a market, softly: How an RBI communique could end India's thriving ETCD market
7 April 2024, The Economic Times

RBI holds firm on rupee derivatives stance, defers norm implementation to May 3
4 April 2024, The Hindu

RBI defers exchange traded currency derivatives norms
5 April 2024, The Indian Express

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News

Share this page