DBMS > EventStoreDB vs. Google Cloud Datastore vs. LevelDB vs. SAP Advantage Database Server vs. searchxml

System Properties Comparison EventStoreDB vs. Google Cloud Datastore vs. LevelDB vs. SAP Advantage Database Server vs. searchxml

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

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

Low-cost RDBMS with access to ISAM and FoxPro data structures

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Native XML DBMS
Search engine

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	4.36
Rank	#72	Overall
	#12	Document stores

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

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

www.eventstore.com

cloud.google.com/datastore

github.com/google/leveldb

www.sap.com/products/advantage-database-server.html

www.searchxml.net/category/products

Technical documentation

developers.eventstore.com

cloud.google.com/datastore/docs

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

www.searchxml.net/support/handouts

Developer

Event Store Limited

Google

Sybase, SAP

informationpartners gmbh

Initial release

2012

2008

2011

1993

2015

Current release

21.2, February 2021

1.23, February 2021

1.0

License

Commercial or Open Source

Open Source

commercial

Open Source

BSD

commercial

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++

Server operating systems

Linux
Windows

hosted

Illumos
Linux
OS X
Windows

Linux
Windows

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (GQL)

yes

APIs and other access methods

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

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Delphi
Perl
PHP

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

using Google App Engine

yes

on the application server

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

yes

sychronisation to multiple collections

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 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

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

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.

caching of (temporary) tables can be configured

User concepts

Access control

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

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

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