DBMS > Coveo vs. Google Cloud Datastore vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. Raima Database Manager

System Properties Comparison Coveo vs. Google Cloud Datastore vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. Raima Database Manager

Editorial information provided by DB-Engines

Name

Description

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Microsofts flagship relational DBMS

Widely used in-process key-value store

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

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS
Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

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

Website

www.coveo.com

cloud.google.com/datastore

www.microsoft.com/en-us/sql-server

www.oracle.com/database/technologies/related/berkeleydb.html

raima.com

Technical documentation

docs.coveo.com

cloud.google.com/datastore/docs

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/cd/E17076_05/html/index.html

docs.raima.com

Developer

Coveo

Google

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Raima Inc.

Initial release

2012

2008

1989

1994

1984

Current release

SQL Server 2022, November 2022

18.1.40, May 2020

15, June 2021

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

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

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

only with the Berkeley DB XML edition

Exporting/Importing of XML structures possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (GQL)

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C#
Java
JavaScript
Python

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

Server-side scripts

Stored procedures

using Google App Engine

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

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

Triggers

yes

Callbacks using the Google Apps Engine

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

yes

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

granular access controls, API key management, content filters

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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

Decreased time-to-market Industry-standard interfaces & tools for making your job...
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Typical application scenarios

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

Infor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
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Market metrics

Over 30 000 applications developers worldwide have field-tested RDM products More...
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Licensing and pricing models

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.