DBMS > Ehcache vs. GeoMesa vs. MarkLogic vs. SingleStore vs. VelocityDB

System Properties Comparison Ehcache vs. GeoMesa vs. MarkLogic vs. SingleStore vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Operational and transactional Enterprise NoSQL database

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Key-value store

Spatial DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

Technical documentation

www.ehcache.org/documentation

www.geomesa.org/documentation/stable/user/index.html

docs.marklogic.com

docs.singlestore.com

velocitydb.com/UserGuide

Developer

Terracotta Inc, owned by Software AG

CCRi and others

MarkLogic Corp.

SingleStore Inc.

VelocityDB Inc

Initial release

2009

2014

2001

2013

2011

Current release

3.10.0, March 2022

5.0.0, May 2024

11.0, December 2022

8.5, January 2024

7.x

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache License 2.0

commercial

restricted free version is available

commercial

free developer edition available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java

Scala

C++

C++, Go

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Linux

64 bit version required

Any that supports .NET

Data scheme

schema-free

yes

schema-free

Schema can be enforced

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

yes

but no triggers and foreign keys

APIs and other access methods

JCache

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

.Net

Supported programming languages

Java

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

Bash
C
C#
Java
JavaScript (Node.js)
Python

.Net

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

yes

Triggers

yes

Cache Event Listeners

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

depending on storage layer

Sharding

hash partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

depending on storage layer

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

can act as a resource manager in an XA/JTA transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

yes

In-memory capabilities

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

yes

depending on storage layer

yes, with Range Indexes

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Role-based access control at the document and subdocument levels

Fine grained access control via users, groups and roles

Based on Windows Authentication

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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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
» more

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

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More resources

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