DBMS > Google Cloud Spanner vs. HEAVY.AI vs. JaguarDB vs. RavenDB vs. VoltDB

System Properties Comparison Google Cloud Spanner vs. HEAVY.AI vs. JaguarDB vs. RavenDB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Performant, highly scalable DBMS for AI and IoT applications

Open Source Operational and Transactional Enterprise NoSQL Document Database

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

cloud.google.com/spanner

github.com/heavyai/heavydb
www.heavy.ai

www.jaguardb.com

ravendb.net

www.voltdb.com

Technical documentation

cloud.google.com/spanner/docs

docs.heavy.ai

www.jaguardb.com/support.html

ravendb.net/docs

docs.voltdb.com

Developer

Google

HEAVY.AI, Inc.

DataJaguar, Inc.

Hibernating Rhinos

VoltDB Inc.

Initial release

2017

2016

2015

2010

Current release

5.10, January 2022

3.3 July 2023

5.4, July 2022

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL V3.0

Open Source

AGPL version 3, commercial license available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++ and CUDA

C++

the server part. Clients available in other languages

Java, C++

Server operating systems

hosted

Linux

Linux
macOS
Raspberry Pi
Windows

Linux
OS X

for development

Data scheme

yes

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

Query statements complying to ANSI 2011

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language (RQL)

yes

only a subset of SQL 99

APIs and other access methods

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
Thrift
Vega

JDBC
ODBC

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/Thrift
Python

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

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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.

Foreign keys

Referential integrity

yes

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Strict serializable isolation

ACID, Cluster-wide transaction available

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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 based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

rights management via user accounts

Authorization levels configured per client per database

Users and roles with access to stored procedures

More information provided by the system vendor

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More resources

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