DBMS > Amazon DynamoDB vs. Apache Impala vs. EJDB vs. HarperDB vs. Manticore Search

System Properties Comparison Amazon DynamoDB vs. Apache Impala vs. EJDB vs. HarperDB vs. Manticore Search

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Analytic DBMS for Hadoop

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Multi-storage database for search, including full-text search.

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Search engine

Secondary database models

Document store

Time Series DBMS

using the Manticore Columnar Library

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

aws.amazon.com/dynamodb

impala.apache.org

github.com/Softmotions/ejdb

www.harperdb.io

manticoresearch.com

Technical documentation

docs.aws.amazon.com/dynamodb

impala.apache.org/impala-docs.html

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

docs.harperdb.io/docs

manual.manticoresearch.com

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Softmotions

HarperDB

Manticore Software

Initial release

2012

2013

2012

2017

Current release

4.1.0, June 2022

3.1, August 2021

6.0, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

Open Source

GPLv2

commercial

free community edition available

Open Source

GPL version 2

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++

Node.js

C++

Server operating systems

hosted

Linux

server-less

Linux
OS X

FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

dynamic schema

Fixed schema

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

JSON data types

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like data manipulation statements

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

in-process shared library

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Custom Functions

since release 3.1

user defined functions

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

yes

the nodes on which a table resides can be defined

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

Atomic execution of specific operations

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

The original contents of fields are not stored in the Manticore index.

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users and roles

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