DBMS > BigObject vs. Microsoft Azure Synapse Analytics vs. RavenDB vs. ToroDB

System Properties Comparison BigObject vs. Microsoft Azure Synapse Analytics vs. RavenDB vs. ToroDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for real-time computations and queries

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Open Source Operational and Transactional Enterprise NoSQL Document Database

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

bigobject.io

azure.microsoft.com/services/synapse-analytics

ravendb.net

github.com/torodb/server

Technical documentation

docs.bigobject.io

docs.microsoft.com/azure/synapse-analytics

ravendb.net/docs

Developer

BigObject, Inc.

Microsoft

Hibernating Rhinos

8Kdata

Initial release

2015

2016

2010

2016

Current release

5.4, July 2022

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

AGPL version 3, commercial license available

Open Source

AGPL-V3

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++

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

Linux
macOS
Raspberry Pi
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

SQL-like DML and DDL statements

yes

SQL-like query language (RQL)

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
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

Supported programming languages

C#
Java
PHP

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

Server-side scripts

Stored procedures

Lua

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate 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.

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

yes

Authorization levels configured per client per database

Access rights for users and roles

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

General Available: Azure Synapse Runtime for Apache Spark 3.4 is now GA | Azure updates
8 April 2024, azure.microsoft.com

Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT | Amazon Web Services
18 October 2023, AWS Blog

Azure Synapse vs. Databricks: Data Platform Comparison 2024
26 March 2024, eWeek

Azure Synapse Runtime for Apache Spark 3.2 End of Support | Azure updates
22 March 2024, azure.microsoft.com

Azure Synapse Analytics: Everything you need to know about Microsoft's cloud analytics platform
24 September 2023, DataScientest

provided by Google News

RavenDB Launches Version 6.0 Lightning Fast Queries, Data Integrations, Corax Indexing Engine, and Sharding
3 October 2023, PR Newswire

RavenDB Welcomes David Baruc as Chief Revenue Officer: Seasoned Tech Leader to Drive Global Sales and ...
13 June 2023, PR Newswire

Oren Eini on RavenDB, Including Consistency Guarantees and C# as the Implementation Language
23 May 2022, InfoQ.com

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

How I Created a RavenDB Python Client
23 September 2016, Visual Studio Magazine

provided by Google News

Share this page