Alternatives to AWS Database Migration Service logo

Alternatives to AWS Database Migration Service

Kafka, Slick, Spring Data, Microsoft SQL Server Management Studio, and DataGrip are the most popular alternatives and competitors to AWS Database Migration Service.
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What is AWS Database Migration Service and what are its top alternatives?

It helps you migrate databases to AWS quickly and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database.
AWS Database Migration Service is a tool in the Database Tools category of a tech stack.

Top Alternatives to AWS Database Migration Service

  • Kafka

    Kafka

    Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design. ...

  • Slick

    Slick

    It is a modern database query and access library for Scala. It allows you to work with stored data almost as if you were using Scala collections while at the same time giving you full control over when a database access happens and which data is transferred. ...

  • Spring Data

    Spring Data

    It makes it easy to use data access technologies, relational and non-relational databases, map-reduce frameworks, and cloud-based data services. This is an umbrella project which contains many subprojects that are specific to a given database. ...

  • Microsoft SQL Server Management Studio

    Microsoft SQL Server Management Studio

    It is an integrated environment for managing any SQL infrastructure, from SQL Server to Azure SQL Database. It provides tools to configure, monitor, and administer instances of SQL Server and databases. Use it to deploy, monitor, and upgrade the data-tier components used by your applications, as well as build queries and scripts. ...

  • DataGrip

    DataGrip

    A cross-platform IDE that is aimed at DBAs and developers working with SQL databases. ...

  • Sequel Pro

    Sequel Pro

    Sequel Pro is a fast, easy-to-use Mac database management application for working with MySQL databases. ...

  • PostGIS

    PostGIS

    PostGIS is a spatial database extender for PostgreSQL object-relational database. It adds support for geographic objects allowing location queries to be run in SQL. ...

  • DBeaver

    DBeaver

    It is a free multi-platform database tool for developers, SQL programmers, database administrators and analysts. Supports all popular databases: MySQL, PostgreSQL, SQLite, Oracle, DB2, SQL Server, Sybase, Teradata, MongoDB, Cassandra, Redis, etc. ...

AWS Database Migration Service alternatives & related posts

Kafka logo

Kafka

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Distributed, fault tolerant, high throughput pub-sub messaging system
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PROS OF KAFKA
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    High-throughput
  • 111
    Distributed
  • 84
    Scalable
  • 77
    High-Performance
  • 62
    Durable
  • 34
    Publish-Subscribe
  • 17
    Simple-to-use
  • 13
    Open source
  • 10
    Written in Scala and java. Runs on JVM
  • 6
    Message broker + Streaming system
  • 4
    Avro schema integration
  • 2
    Suport Multiple clients
  • 2
    KSQL
  • 2
    Partioned, replayable log
  • 1
    Fun
  • 1
    Extremely good parallelism constructs
  • 1
    Simple publisher / multi-subscriber model
  • 1
    Robust
CONS OF KAFKA
  • 25
    Non-Java clients are second-class citizens
  • 25
    Needs Zookeeper
  • 7
    Operational difficulties
  • 1
    Terrible Packaging

related Kafka posts

Eric Colson
Chief Algorithms Officer at Stitch Fix · | 20 upvotes · 1.7M views

The algorithms and data infrastructure at Stitch Fix is housed in #AWS. Data acquisition is split between events flowing through Kafka, and periodic snapshots of PostgreSQL DBs. We store data in an Amazon S3 based data warehouse. Apache Spark on Yarn is our tool of choice for data movement and #ETL. Because our storage layer (s3) is decoupled from our processing layer, we are able to scale our compute environment very elastically. We have several semi-permanent, autoscaling Yarn clusters running to serve our data processing needs. While the bulk of our compute infrastructure is dedicated to algorithmic processing, we also implemented Presto for adhoc queries and dashboards.

Beyond data movement and ETL, most #ML centric jobs (e.g. model training and execution) run in a similarly elastic environment as containers running Python and R code on Amazon EC2 Container Service clusters. The execution of batch jobs on top of ECS is managed by Flotilla, a service we built in house and open sourced (see https://github.com/stitchfix/flotilla-os).

At Stitch Fix, algorithmic integrations are pervasive across the business. We have dozens of data products actively integrated systems. That requires serving layer that is robust, agile, flexible, and allows for self-service. Models produced on Flotilla are packaged for deployment in production using Khan, another framework we've developed internally. Khan provides our data scientists the ability to quickly productionize those models they've developed with open source frameworks in Python 3 (e.g. PyTorch, sklearn), by automatically packaging them as Docker containers and deploying to Amazon ECS. This provides our data scientist a one-click method of getting from their algorithms to production. We then integrate those deployments into a service mesh, which allows us to A/B test various implementations in our product.

For more info:

#DataScience #DataStack #Data

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John Kodumal

As we've evolved or added additional infrastructure to our stack, we've biased towards managed services. Most new backing stores are Amazon RDS instances now. We do use self-managed PostgreSQL with TimescaleDB for time-series data—this is made HA with the use of Patroni and Consul.

We also use managed Amazon ElastiCache instances instead of spinning up Amazon EC2 instances to run Redis workloads, as well as shifting to Amazon Kinesis instead of Kafka.

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Slick logo

Slick

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Database query and access library for Scala
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PROS OF SLICK
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    CONS OF SLICK
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      related Slick posts

      Spring Data logo

      Spring Data

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      Provides a consistent approach to data access – relational, non-relational, map-reduce, and beyond
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      PROS OF SPRING DATA
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        CONS OF SPRING DATA
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          related Spring Data posts

          Остап Комплікевич

          I need some advice to choose an engine for generation web pages from the Spring Boot app. Which technology is the best solution today? 1) JSP + JSTL 2) Apache FreeMarker 3) Thymeleaf Or you can suggest even other perspective tools. I am using Spring Boot, Spring Web, Spring Data, Spring Security, PostgreSQL, Apache Tomcat in my project. I have already tried to generate pages using jsp, jstl, and it went well. However, I had huge problems via carrying already created static pages, to jsp format, because of syntax. Thanks.

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          Microsoft SQL Server Management Studio logo

          Microsoft SQL Server Management Studio

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          An integrated environment for managing any SQL infrastructure
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          PROS OF MICROSOFT SQL SERVER MANAGEMENT STUDIO
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            CONS OF MICROSOFT SQL SERVER MANAGEMENT STUDIO
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              related Microsoft SQL Server Management Studio posts

              Kelsey Doolittle

              We have a 138 row, 1700 column database likely to grow at least a row and a column every week. We are mostly concerned with how user-friendly the graphical management tools are. I understand MySQL has MySQL WorkBench, and Microsoft SQL Server has Microsoft SQL Server Management Studio. We have about 6 months to migrate our Excel database to one of these DBMS, and continue (hopefully manually) importing excel files from then on. Any tips appreciated!

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              DataGrip logo

              DataGrip

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              A database IDE for professional SQL developers
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              PROS OF DATAGRIP
              • 3
                Works on Linux, Windows and MacOS
              • 2
                Wide range of DBMS support
              • 1
                Code completion
              • 1
                Generate ERD
              • 1
                Quick-fixes using keyboard shortcuts
              • 1
                Code analysis
              • 1
                Database introspection on 21 different dbms
              • 1
                Export data using a variety of formats using open api
              • 1
                Import data
              • 1
                Diff viewer
              CONS OF DATAGRIP
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                related DataGrip posts

                Sequel Pro logo

                Sequel Pro

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                MySQL database management for Mac OS X
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                PROS OF SEQUEL PRO
                • 23
                  Free
                • 18
                  Simple
                • 17
                  Clean UI
                • 8
                  Easy
                CONS OF SEQUEL PRO
                  Be the first to leave a con

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                  PostGIS logo

                  PostGIS

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                  Open source spatial database
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                  PROS OF POSTGIS
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                    De facto GIS in SQL
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                    Good Documentation
                  CONS OF POSTGIS
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                    DBeaver logo

                    DBeaver

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                    A Universal Database Tool
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                    PROS OF DBEAVER
                    • 8
                      Free
                    • 7
                      Platform independent
                    • 4
                      Import-Export Data
                    • 4
                      Automatic driver download
                    • 3
                      Move data between databases
                    • 2
                      Wide range of DBMS support
                    • 2
                      Simple to use
                    • 1
                      SAP Hana DB support
                    • 1
                      Themes
                    CONS OF DBEAVER
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                      related DBeaver posts

                      Manikandan Shanmugam
                      Software Engineer at Blitzscaletech Software Solution · | 4 upvotes · 104K views
                      Shared insights
                      on
                      AzureDataStudioAzureDataStudioDBeaverDBeaver

                      Which tools are preferred if I choose to work on more data side? Which one is good if I decide to work on web development? I'm using DBeaver and am now considering a move to AzureDataStudio to break the monotony while working. I would like to hear your opinion. Which one are you using, and what are the things you are missing in dbeaver or data studio.

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