DBMS > AgensGraph vs. EXASOL vs. Google Cloud Spanner vs. JaguarDB vs. Snowflake

System Properties Comparison AgensGraph vs. EXASOL vs. Google Cloud Spanner vs. JaguarDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Performant, highly scalable DBMS for AI and IoT applications

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Key-value store
Vector DBMS

Relational 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	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

bitnine.net/agensgraph

www.exasol.com

cloud.google.com/spanner

www.jaguardb.com

www.snowflake.com

Technical documentation

bitnine.net/documentation

www.exasol.com/resources

cloud.google.com/spanner/docs

www.jaguardb.com/support.html

docs.snowflake.net/manuals/index.html

Developer

Bitnine Global Inc.

Exasol

Google

DataJaguar, Inc.

Snowflake Computing Inc.

Initial release

2016

2000

2017

2015

2014

Current release

2.1, December 2018

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

GPL V3.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

the server part. Clients available in other languages

Server operating systems

Linux
OS X
Windows

hosted

Linux

hosted

Data scheme

depending on used data model

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

Cypher Query Language
JDBC

.Net
JDBC
ODBC
WebSocket

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

Java
Lua
Python
R

Go
Java
JavaScript (Node.js)
Python

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication with 3 replicas for regional instances.

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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