DBMS > Lovefield vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. Raima Database Manager vs. Vertica

System Properties Comparison Lovefield vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. Raima Database Manager vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Globally distributed, horizontally scalable, multi-model database service

A Wide Column Store for rapid development using massive semi-structured datasets

RDBMS with a small footprint, either embedded into an application or used as a database server

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Relational DBMS
Time Series DBMS

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.49
Rank	#259	Overall
	#121	Relational DBMS
	#21	Time Series DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

google.github.io/lovefield

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/services/storage/tables

raima.com

www.vertica.com

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

learn.microsoft.com/azure/cosmos-db

docs.raima.com

vertica.com/documentation

Developer

Google

Microsoft

Raima Inc.

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2014

2012

1984

2005

Current release

2.1.12, February 2017

15, June 2021

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

Android
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows

Linux

Data scheme

yes

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

JSON types

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.

Exporting/Importing of XML structures possible

Secondary indexes

yes

All properties auto-indexed by default

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

JavaScript

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

.Net
C
C++
Objective-C
PL/SQL

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

JavaScript

yes

based on the ANSI/ISO SQL Persistent Stored Modules (PSM) specification

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

Using read-only observers

JavaScript

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

horizontal partitioning

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Raima Database Manager (RDM) is an embedded time-series database optimized to run...
» more

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Decreased time-to-market Industry-standard interfaces & tools for making your job...
» more

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Typical use cases include: Internet of Things (IoT) Embedded In-Memory Database Time-Series...
» more

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Infor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
» more

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Market metrics

Over 30 000 applications developers worldwide have field-tested RDM products More...
» more

Licensing and pricing models

Just as the technical aspects of Raima Database Manager are flexible, so are the...
» more

Cost-based models and subscription-based models are both available. One license is...
» more

News

Raima Unveils RaimaDB 16.0: Elevating Database Performance and User Experience
29 February 2024

Raima Announces Release of Raima Database Manager (RDM) v15, a Powerful Embedded Time Series Database
10 June 2021

Raima Announces Release of Raima Database Manager (RDM) v14.2, a Powerful IoT Edge Embedded Database
8 October 2020

Raima Joins BlackBerry QNX Channel Partner Program to Deliver Safety-Critical and Secure Software Solutions
1 October 2020

Raima Expands Their Reseller Network in Asia
19 May 2020

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.