Google Cloud Datastore is a NoSQL "schemaless" database as a service, supporting diverse data types. The database is managed; Google manages sharding and replication and prices according to storage and activity.
N/A
IBM DataStage
Score 7.7 out of 10
N/A
IBM® DataStage® is a data integration tool that helps users to design, develop and run jobs that move and transform data. At its core, the DataStage tool supports extract, transform and load (ETL) and extract, load and transform (ELT) patterns. A basic version of the software is available for on-premises deployment, and the cloud-based DataStage for IBM Cloud Pak® for Data offers automated integration capabilities in a hybrid or multicloud environment.
N/A
Pricing
Google Cloud Datastore
IBM DataStage
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Google Cloud Datastore
IBM DataStage
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
—
More Pricing Information
Community Pulse
Google Cloud Datastore
IBM DataStage
Features
Google Cloud Datastore
IBM DataStage
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Google Cloud Datastore
10.0
2 Ratings
12% above category average
IBM DataStage
-
Ratings
Performance
10.02 Ratings
00 Ratings
Availability
10.02 Ratings
00 Ratings
Concurrency
10.02 Ratings
00 Ratings
Security
10.02 Ratings
00 Ratings
Scalability
10.02 Ratings
00 Ratings
Data model flexibility
10.02 Ratings
00 Ratings
Deployment model flexibility
9.92 Ratings
00 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Google Cloud Datastore
-
Ratings
IBM DataStage
8.1
11 Ratings
2% below category average
Connect to traditional data sources
00 Ratings
8.411 Ratings
Connecto to Big Data and NoSQL
00 Ratings
7.910 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Google Cloud Datastore
-
Ratings
IBM DataStage
7.7
11 Ratings
5% below category average
Simple transformations
00 Ratings
8.011 Ratings
Complex transformations
00 Ratings
7.511 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Google Cloud Datastore
-
Ratings
IBM DataStage
7.0
11 Ratings
11% below category average
Data model creation
00 Ratings
6.68 Ratings
Metadata management
00 Ratings
5.010 Ratings
Business rules and workflow
00 Ratings
7.110 Ratings
Collaboration
00 Ratings
7.111 Ratings
Testing and debugging
00 Ratings
6.511 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
If you want a serverless NoSQL database, no matter it is for personal use, or for company use, Google Cloud Datastore should be on top of your list, especially if you are using Google Cloud as your primary cloud platform. It integrates with all services in the Google Cloud platform.
DataStage is somewhat outdated for an ETL. I guess that's what makes it a bit lagged behind its competitors. It can be used for data processing, sure, but its performance seems to be lagging behind or quite slow given the server it is running from. I won’t depend on this application if it's handling a lot of mission-critical banking and business data.
Technical support is a key area IBM should improve for this product. Sometimes our case is assigned to a support engineer and he has no idea of the product or services.
Provide custom reports for datastage jobs and performance such as job history reports, warning messages or error messages.
Make it fully compatible with Oracle and users can direct use of Oracle ODBC drivers instead of Data Direct driver. Same for SQL server.
For the amount of use we're getting from Google Cloud Datastore, switching to any other platform would have more cost with little gain. Not having to manage and maintain Google Cloud Datastore for over 4 years has allowed our teams to work on other things. The price is so low that almost any other option for our needs would be far more expensive in time and money.
Because it is robust, and it is being continuously improved. DS is one of the most used and recognized tools in the market. Large companies have implemented it in the first instance to develop their DW, but finding the advantages it has, they could use it for other types of projects such as migrations, application feeding, etc.
It could load thousands of records in seconds. But in the Parallel version, you need to understand how to particionate the data. If you use the algorithms erroneously, or the functionalities that it gives for the parsing of data, the performance can fall drastically, even with few records. It is necessary to have people with experience to be able to determine which algorithm to use and understand why.
IBM offers different levels of support but in my experience being and IBM shop helps to get direct support from more knowledgeable technicians from IBM. Not sure on the cost of having this kind of support, but I know there's also general support and community blogs and websites on the Internet make it easy to troubleshoot issues whenever there's need for that.
We selected Google Cloud Datastore as one of our candidates for our NoSQL data is because it is provided by Google Cloud, which fits our needs. Most of our infrastructure is on Google Cloud, so when we think about the NoSQL database, the first thing we thought about is Google Cloud Datastore. And it proves itself.
With effective capabilities and easy to manipulate the features and easy to produce accurate data analytics and the Cloud services Automation, this IBM platform is more reliable and easy to document management. The features on this platform are equipped with excellent big data management and easy to provide accurate data analytics.
It’s hard to say at this point, it delivers, but not quite as I expected. It takes a lot of resources to manage and sort this out (manpower, financial).
Definitely, I don’t have the exact numbers, but given the data it processes, it is A LOT. So props to the developer of this application.
Again, based on my experience, I’d choose other ETL apps if there is one that's more user-friendly.