DBMS > AgensGraph vs. Amazon DynamoDB vs. LevelDB vs. RocksDB vs. Splice Machine

System Properties Comparison AgensGraph vs. Amazon DynamoDB vs. LevelDB vs. RocksDB vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Graph DBMS
Relational DBMS

Document store
Key-value store

Key-value store

Relational DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/dynamodb

github.com/google/leveldb

rocksdb.org

splicemachine.com

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/dynamodb

github.com/google/leveldb/blob/main/doc/index.md

github.com/facebook/rocksdb/wiki

splicemachine.com/how-it-works

Developer

Bitnine Global Inc.

Amazon

Google

Facebook, Inc.

Splice Machine

Initial release

2016

2012

2011

2013

2014

Current release

2.1, December 2018

1.23, February 2021

9.2.1, May 2024

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free tier for a limited amount of database operations

Open Source

BSD

Open Source

BSD

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Server operating systems

Linux
OS X
Windows

hosted

Illumos
Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

depending on used data model

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Cypher Query Language
JDBC

RESTful HTTP API

C++ API
Java API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
Java
JavaScript
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Go
Java
Perl
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

with automatic compression on writes

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

fine grained access rights according to SQL-standard

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

Access rights for users, groups and roles according to SQL-standard

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