Relate to LinearSVC() and SGDClassifier()

I ran both with a subset of my 33k-samples by 30k-features and I am 
getting a huge difference in results. Is this expected behavour!

After 10-fold-cross-validation (using the Defaults as arguments in both 
cases) I am getting:

Accuracy = 44% for SGD
Accuracy = 89% for LinearSVC


This is the modules I called
csvm = svm.LinearSVC()
csvm.fit(X, y)
csvm.score(crossv_X, crossv_y)

sgd = linear_model.SGDClassifier()
sgd.fit(X, y)
sgd.score(crossv_X, crossv_y)



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