DBMS > EJDB vs. Oracle Coherence vs. SAP SQL Anywhere vs. SQLite vs. Vertica

System Properties Comparison EJDB vs. Oracle Coherence vs. SAP SQL Anywhere vs. SQLite vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Oracles in-memory data grid solution

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Widely used embeddable, in-process RDBMS

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

Document store

Key-value store

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

github.com/Softmotions/ejdb

www.oracle.com/java/coherence

www.sap.com/products/technology-platform/sql-anywhere.html

www.sqlite.org

www.vertica.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

docs.oracle.com/en/middleware/standalone/coherence

help.sap.com/docs/SAP_SQL_Anywhere

www.sqlite.org/docs.html

vertica.com/documentation

Developer

Softmotions

Oracle

SAP

formerly Sybase

Dwayne Richard Hipp

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

2007

1992

2000

2005

Current release

14.1, August 2023

17, July 2015

3.46.0 (23 May 2024), May 2024

12.0.3, January 2023

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Public Domain

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

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

Java

C++

Server operating systems

server-less

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows

server-less

Linux

Data scheme

schema-free

yes

dynamic column types

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

string, integer, double, bool, date, object_id

yes

not rigid because of 'dynamic typing' concept.

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

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

SQL

Support of SQL

yes

SQL-92 is not fully supported

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

APIs and other access methods

in-process shared library

JCache
JPA
RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

character-based, interactive, front-end utility

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
C++
Java

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

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

Server-side scripts

Stored procedures

yes, in C/C++, Java, .Net or Perl

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

Live Events

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

Source-replica replication

Database mirroring

none

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

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

optionally

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

authentification to access the cache via certificates or http basic authentication

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Licensing and pricing models

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