DBMS > AgensGraph vs. Apache Phoenix vs. RavenDB vs. SAP HANA vs. Spark SQL

System Properties Comparison AgensGraph vs. Apache Phoenix vs. RavenDB vs. SAP HANA vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

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

A scale-out RDBMS with evolutionary schema built on Apache HBase

Open Source Operational and Transactional Enterprise NoSQL Document Database

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Document store

Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

bitnine.net/agensgraph

phoenix.apache.org

ravendb.net

www.sap.com/products/hana.html

spark.apache.org/sql

Technical documentation

bitnine.net/documentation

phoenix.apache.org

ravendb.net/docs

help.sap.com/hana

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

Developer

Bitnine Global Inc.

Apache Software Foundation

Hibernating Rhinos

SAP

Apache Software Foundation

Initial release

2016

2014

2010

2014

Current release

2.1, December 2018

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

5.4, July 2022

2.0 SPS07 (April 4, 2023), April 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

Open Source

AGPL version 3, commercial license available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Scala

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

Linux
macOS
Raspberry Pi
Windows

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

depending on used data model

yes

late-bound, schema-on-read capabilities

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 query language (RQL)

yes

SQL-like DML and DDL statements

APIs and other access methods

Cypher Query Language
JDBC

JDBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

yes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Authorization levels configured per client per database

yes

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